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Machine Learning Engineer 4 - Finance Tech\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. \n \n By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.\n, • 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment\n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code\n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 6 years of experience programming with Python, Java, Golang, or C++\n, • At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans\n, • 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models\n, • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents\n, • Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5\n \n Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description Quest International | Field Service Engineer I – New York, New Jersey & Pennsylvania Pay: $20.00–$29.00 per hour, depending on experience and qualifications, plus applicable overtime Employment Type: Full-Time, Temp-to-Hire Location: Field-Based – New York, New Jersey & Pennsylvania Service Territory Travel: Up to 80%, including overnight assignments Start Date: ASAP Build Your Career in Technical Field Service Quest International, Inc. is seeking a Field Service Engineer I to install, maintain, troubleshoot, and repair medical and industrial equipment at customer locations throughout the assigned service territory. You do not need previous biomedical equipment experience to qualify. If you have hands-on experience repairing electronics, industrial equipment, or electro-mechanical systems, we encourage you to apply. We also welcome candidates with relevant military technical training in electronics, avionics, or equipment maintenance. Quest provides equipment-specific technical training to help qualified technicians develop the skills needed to service assigned customer equipment. What You'll Do Install, inspect, maintain, troubleshoot, and repair medical, electronic, and electro-mechanical equipment at customer sites. Perform preventive maintenance, corrective repairs, and functional testing. Diagnose electrical and mechanical failures using digital multimeters, wiring diagrams, schematics, and service manuals. Troubleshoot equipment to the Field Replaceable Unit (FRU), module, assembly, or component level. Identify and repair problems involving wiring harnesses, sensors, power supplies, motors, and sensitive electronic components. Replace defective boards, modules, wiring assemblies, and other serviceable parts. Verify equipment operation according to manufacturer specifications. Maintain accurate electronic work orders, service reports, and repair documentation. Communicate professionally with customers and coordinate with Quest's technical support and dispatch teams. Required Qualifications High school diploma or equivalent. At least one year of relevant hands-on equipment repair, electronics, electrical, electro-mechanical maintenance, or field-service experience. Demonstrated ability to troubleshoot electronic, electrical, or electro-mechanical equipment. Experience using a digital multimeter or comparable diagnostic equipment. Familiarity with schematics, wiring diagrams, service manuals, and technical instructions. Ability to diagnose equipment failures and replace defective components. Basic computer skills, including Windows, Microsoft Office, and electronic service documentation. Strong problem-solving, communication, and customer-service skills. Ability to work independently at customer locations with appropriate technical support. Preferred Qualifications The following experience is helpful but not required: Biomedical equipment repair or medical device service. Industrial electronics, automation, or electro-mechanical maintenance. Optical equipment or electronic instrumentation. Original Equipment Manufacturer (OEM) equipment service. Military electronics, avionics, or electro-mechanical training. Associate degree or technical certificate in electronics or a related field. Experience with frequency counters, vacuum/pressure meters, or other service instruments. Familiarity with command-line tools or PowerShell. Travel and Transportation Requirements This is a field-based position, not a work-from-home position. Must reside within the approved service territory or have confirmed relocation arrangements before employment begins. Must possess a valid driver's license and acceptable driving record. Must have a reliable personal vehicle and appropriate automobile insurance. Must be willing to travel up to 80%, including overnight assignments. Must be available for occasional nonstandard work hours and changing customer schedules. Must be able to perform the essential functions of the position, with or without reasonable accommodation. Must be willing to complete applicable pre-employment requirements, including Quest's required Human Performance Test. Why Join Quest International? $20.00–$29.00 per hour DOE, plus applicable overtime. Equipment-specific technical training. Opportunities to develop skills in medical and industrial equipment service. Professional development and potential career advancement. Hands-on technical work supporting a variety of customer equipment. Employee Benefits Eligible employees may participate in Quest International's benefit programs, which may include: Medical, dental, and vision insurance. Life insurance and accidental death and dismemberment coverage. Short-term and long-term disability insurance. Healthcare and dependent-care flexible spending accounts. Voluntary supplemental insurance programs. All benefits are subject to applicable eligibility requirements, employment classification, plan provisions, enrollment periods, coverage dates, and employee contributions. Benefit eligibility during the temporary-to-hire period depends on the applicable employer's plans. About Quest International For more than 40 years, Quest International, Inc. has provided technical service, equipment repair, maintenance, logistics, and support solutions to healthcare organizations, medical equipment manufacturers, and technology companies. Our Field Service team helps customers maintain reliable equipment through installation, preventive maintenance, troubleshooting, and corrective repairs. Apply Today If you enjoy diagnosing technical problems, repairing equipment, and working independently in the field, we encourage you to apply. Biomedical experience is not required when you have relevant hands-on technical repair experience. Join Quest International and put your technical skills to work. Quest International, Inc. www.questinc.com Quest International is an Equal Opportunity Employer.

Job Description About Bell and Howell Bell and Howell delivers technology-driven Automation Services and Automation Solutions that help businesses optimize performance, reduce downtime, and improve customer experiences. Our Automation Services bring a dedicated team of expert mechatronic service engineers completely covering North America and backed by our Integrated 360™ advanced technology enabling remote repair, diagnostics, automated SmartOps Dispatch™ and 24/7/365 technical assistance for our clients. We provide a comprehensive and certified level of support for thousands of diversified clients. Our Automated Solutions product portfolio consists of next-generation equipment delivering best-in-class performance enhancing workflow efficiency and elevating customer experiences across multiple markets including retail, pharmaceuticals, packaging, mail production, ecommerce and manufacturing – all backed by the best service in the industry. Location: NYC/Brooklyn/Queens & Long Island Areas Hourly Range: 23-30/hr. Summary: The Field Customer Service Engineer serves as primary customer contact on technical and service-related problems on a wide range of industrial, robotic and printing equipment. Diagnoses electronic, mechanical, software and system failures, using established procedures provided by our highly rated service training department. This job may include any aspect of field support, including electrical/electronics, hardware, software, PC’s, and networking. Provides technical support to customers on operational or maintenance aspects of system equipment. Determines most cost-effective repair/resolution to minimize customer downtime. Note: This is not an IT role. The position requires hands-on electrical and mechanical troubleshooting with experience using Digital Multi Meter (DMM) and more. Duties and Responsibilities: • Primary responsibility will be to install, troubleshoot and repair a variety of industrial products that include, but are not limited to; printing and packaging equipment, cash recycling products, inserting and sorting machines, credit card attaching and processing systems, robotics and any other applicable third-party accessories attached as part of the system., • Schedule and perform regular predictive/preventive maintenance inspections on equipment., • Provide support by managing parts inventory, customer service calls and preventative maintenance schedules., • Foster positive customer relations and a high degree of customer satisfaction by communicating effectively with customers., • Act as a liaison between the customer and other departments/functions of the company., • May need to provide an “on call” level of service up to seven (7) day/week twenty-four (24) hour/day for emergency customer assistance; respond to emergency and non-scheduled calls for service within established response time goals. Supervisory Responsibilities: N/A Competencies (Skills, Knowledge and Abilities): • Requires understanding of computer program functionality and software troubleshooting skills., • Strong interpersonal/customer relation skills., • Ability to build and maintain strong customer relationships by understanding their operations and instilling confidence with effective proactive communication., • Ability to effectively resolve conflict internally and externally., • Ability to accomplish the describe duties through appropriate hand, power, and testing tools/equipment., • Ability to reason logically and make sound decisions along with considering alternative and diverse perspectives., • Strong analytical, problem-solving, quantitative, and time management skills., • Ability to communicate effectively both orally and in writing., • Ability to understand, remember and follow verbal and written instructions., • Ability to work as an integral part of a team., • Ability to read and understand written procedures and diagrams for assembly and test., • Ability to develop and implement solutions to assembly problem., • Ability to maintain regular attendance and be punctual. Education and Experience: • High School degree or equivalent with 2-year degree or diploma in electronics/advanced mechanics/software training with 1+ years related industry/equipment experience, or equivalent combination of education and experience., • Requires strong electronics and mechanical background, understanding of computer program functionality and software troubleshooting skills, • Associate degree preferred. Travel: This position requires minimal travel in the United States and Canada for training and other requirements. For field only, local travel time could be greater than 50%. Physical Requirements: • Ability to use standard and specialized hand, power and diagnostic tools and measuring equipment, such as oscilloscopes, DMM, gauges, etc., • Requires lifting to waist seventy (70) pounds., • Requires walking and standing; using hands to feel objects; reaching; and requires balance., • Requires bending, stooping, kneeling, crouching and/or crawling for periods of time., • Ability to work in a loud environment., • Ability to work in small, cramped areas., • Ability to work in elevated environment up to twenty (20) feet., • Work is performed in a controlled office, retail, and manufacturing environment; noise within acceptable safety levels; paper dust prevalent; cleaners and solvents used to clean machines; machines contain moving parts. Other Duties Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. Bell and Howell is an Equal Opportunity Employer. It is company policy to administer employment based solely on an individual’s qualifications, ability and performance without regard to race, color, religion, gender identity, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, age, national origin or ancestry, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed servicemember status, marital status, or any other characteristic protected by federal, state or local law.

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 4 - Manager IC\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One—ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging.\n, • 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization.\n, • 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus).\n, • 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (Gen AI Platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (Gen AI SDK: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n What You’ll Do: \n \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n \n Basic Qualifications: \n \n \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n \n \n Preferred Qualifications: \n \n \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (FM Hosting, LLM Inference)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Foundations)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (AI Foundations, VLM Customization)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. \n \n Team: \n The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.\n, • 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4\n \n Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (AI Foundations: Evaluations and Agentic Workflows)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. \n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Safety and Multimodal)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are experienced in AI red teaming and in deploying safety guardrails for multimodal systems, including VLMs, MLLMs, and MM-RAG architectures\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in AI Safety and LLM safety alignment\n, • Experience with Safety and vulnerability assessment of Multi-modal application using image/video plus text modality\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: CrowdStrike Falcon is the industry standard in cloud‑native cybersecurity and threat hunting, processing trillions of events per day. As a Principal SRE, you will operate at the intersection of our Core Platform and Embedded Reliability charters: building the foundational libraries, services, and tooling that every product group depends on, while embedding directly with product engineering teams and their leadership to drive reliability outcomes at scale. While we embrace the SRE moniker, at CrowdStrike it means something far more service‑oriented and engineering‑heavy than traditional operations. This is hands‑on systems engineering — writing production code, re‑architecting critical systems, and eliminating entire classes of failure — not ticket management. It is far and away our most self‑driven and autonomous backend engineering role, with the freedom to move up, down, and laterally across the stack as needed. You'll join a group with bottom‑up visibility and ownership of a fast‑expanding codebase (including AI‑based Detection & Response) and a far‑reaching mandate for service resiliency. Several key feature additions and critical re‑architecture initiatives are underway: deploying core services to additional cloud providers, modularizing into reusable components, improving core libraries and frameworks, maturing observability tooling (tracing, profiling, alerting, SLOs), and automating away manual toil across all of the above. Recent examples of the team's work include introducing adaptive concurrency into our core Kafka library to implement flow control that protects database performance, resolving critical issues in leader election libraries, and building infrastructure‑as‑code tooling that eliminated manual deployment processes. At the Senior Engineer level, your influence is organizational. Product engineers and engineering leaders will come to you for guidance on architectural decisions because you've earned credibility through hands‑on work and delivered results. You will shape architectural choices that affect every feature development team and provide shared architectural components leveraged throughout the Falcon Platform — including Unified Search, Protobuf libraries, and other shared‑tier infrastructure. Why This Role Matters: Our customers depend on us to protect their businesses from sophisticated threats, and reliability isn't optional — it's fundamental to our mission. Your work directly impacts whether organizations around the world can defend themselves against cyberattacks. You'll work on problems that matter, at a scale few companies can match, with the autonomy to make real architectural decisions. Location: This position requires candidates to be based in Midtown Manhattan, NY; Redmond, WA; Sunnyvale, CA; or Austin, TX. It's a hybrid role, with employees typically working 2 to 3 days per week in the office. What You'll Do: • Partner with engineering leadership across multiple product groups to define and drive multi‑year reliability roadmaps., • Design and implement architectural improvements to services, libraries, and platforms that impact teams across all of CrowdStrike., • Develop and maintain services that meet aggressive reliability and scalability demands., • Extend and build new libraries for cross‑cutting concerns spanning CrowdStrike's cloud platform, which comprises hundreds of libraries and services., • Lead initiatives around reliability, scalability, performance, and cost efficiency in large‑scale distributed systems., • Establish foundational observability practices: ensure teams instrument services properly, react to signals effectively, and leverage observability to drive automation such as continuous delivery., • Define and implement service‑level objectives and error budgets that drive real decision‑making and prioritization., • Lead performance and cost optimization efforts: profiling, bottleneck analysis, capacity planning, and cloud efficiency improvements., • Conduct resilience engineering: chaos experiments, failure injection, failure modeling, and designing for graceful degradation., • Design and implement automation and infrastructure‑as‑code to improve infrastructure reliability and eliminate manual toil., • Provide technical leadership during complex incidents and ensure follow‑through on retrospectives with concrete improvements that eliminate entire classes of failures., • Identify opportunities to extract common patterns into shared libraries and tools, or partner with platform teams on improvements benefiting multiple product groups., • Continuously re‑evaluate our products to improve architecture, knowledge models, developer and user experience, performance, and stability., • Drive strategic technical decisions and influence infrastructure and operational improvements across the organization., • Mentor and coach engineers, raising the technical IQ of the team and driving architectural standards across the org., • Use and give back to the open source community; evangelize software engineering best practices, especially as they pertain to Go., • Brainstorm, define, and build collaboratively with members across multiple teams as an energetic self‑starter who owns and is accountable for deliverables. What You'll Need: • 10+ years of experience building and operating distributed systems and service‑oriented backends at scale., • 5+ years developing microservices for a SaaS product in a modern backend language (Go, Java, Scala, Kotlin, Python, Node.js)., • Expert‑level proficiency in at least one programming language, with expert‑level Go or demonstrated ability and willingness to reach expert level in Go., • Deep understanding of distributed systems: consensus algorithms, replication, consistency models, failure modes, and scalability patterns., • Proven experience scaling backend systems — sharding, partitioning, horizontal scaling, capacity planning, and performance optimization are second nature., • Deep understanding of multi‑threading, concurrency, and parallel processing., • Track record of making impactful architectural decisions at organizational scope and seeing them through to production., • Strong systems thinking and the ability to influence without direct authority across organizational boundaries., • Thorough command of engineering best practices: appropriate testing paradigms, effective peer code review, and resilient architecture., • Ability to thrive in a fast‑paced, test‑driven, collaborative, and iterative environment; strong team‑player orientation., • A desire to ship code and a love of seeing your bits run in production., • Degree in Computer Science, or commensurate experience in data structures, algorithms, and distributed systems., • Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes. Bonus Points: • Experience driving reliability improvements in organizations with hundreds or thousands of microservices., • Deep knowledge of Kubernetes or other large‑scale orchestration systems., • Hands‑on experience with AWS, Cassandra, Kafka, Elasticsearch/OpenSearch, or similar large‑scale distributed technologies., • Experience with Google Cloud Platform (GCP)., • Experience with Oracle Cloud Infrastructure (OCI)., • Experience delivering or operating services across multiple cloud providers, including multi‑cloud abstraction layers, portability, and cloud‑agnostic tooling., • Track record of building internal platforms, developer platforms, or tools that other engineers depend on., • Experience with infrastructure cost optimization at scale., • Background in performance engineering: profiling, optimization, and identifying system bottlenecks., • Experience with chaos engineering or resilience testing practices., • History of establishing SLO/SLI frameworks and error budgets in production environments., • Contributions to the open source community (GitHub, Stack Overflow, technical blogging)., • Prior experience in the cybersecurity or intelligence fields. #LI-NA1 Benefits of Working at CrowdStrike: Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at _ for further assistance. _ CrowdStrike participates in the E-Verify program. _ _ CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 - $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please _.

Sr. Staff AI Engineer\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale\n, • Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide\n, • Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture\n, • Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies\n, • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy\n, • 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership\n, • Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance\n, • Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams\n, • Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. The CrowdStrike Cloud Detection Engine (CDE) team is building a powerful, next-generation platform designed to be a force multiplier for security teams. Our platform empowers customers who leverage multiple Falcon products to create and manage advanced, unified detections and content. This core platform capability is a strategic imperative for CrowdStrike, aiming to provide a competitive advantage that is difficult to replicate, ensuring our customers have unparalleled detection and response capabilities across the entire Falcon ecosystem. We build the real-time data systems behind CrowdStrike's detection pipeline. Our team owns the streaming engine that processes all first-party sensor telemetry and maintains a petabyte-scale graph of real-time system activity, and the distributed correlation engine that evaluates trillions of events a day to catch multi-stage attacks that no single event can surface. Both systems are at the core of how CrowdStrike finds adversaries. We're looking for someone who is excited about working in systems programming: custom query languages, graph databases, state machines, performance work where microseconds matter. We ship fast, we build with modern tooling including AI in our dev workflow, and own everything end to end from design to production This role is hybrid, requiring 2-3 days per week on-site at the posted location. About the Role: We are seeking a Senior Engineer II to join the CDE Platform team. In this role, you will be instrumental in designing, building, and scaling the foundational services that orchestrate data, content, and execution logic across CrowdStrike’s products (e.g., NGSIEM, FCS, Endpoint). You will be a key driver in creating a highly performant, scalable, and resilient platform that processes internet-scale data streams and enables real-time detection generation. What You'll Do: • Lead backend engineering efforts from rapid prototypes to large-scale applications across CrowdStrike products, • Leverage and build cloud-based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale, • Brainstorm, define and build collaboratively with members across multiple teams, • Obsess about learning, and champion the newest technologies & tricks with others, raising the technical IQ of the team, • Be mentored and mentor other developers on web, backend, and data storage technologies and our system, • Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability, • Be given the autonomy to own your work in a high trust environment The technology stack you’ll use will include: • Go (Golang) or C++, • AWS/GCP/Azure/Kubernetes, • Kafka, • GIT, • Cassandra, • Docker, • Redis What You'll Need: • Degree in Computer Science (or professional experience in data structures/algorithms/distributed systems), • Understanding scalability and distributed systems i.e. sharding, partitioning, concurrency, etc, • Being a team player, • A thorough understanding of engineering best practices from appropriate testing paradigms to effective peer code reviews and resilient architecture., • The ability to thrive in a fast-paced, test-driven, collaborative and iterative programming environment., • The skills to meet your commitments on time and produce high-quality software that is unit tested, code reviewed and checked in regularly for continuous integration., • Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes. Bonus Points: • Contributions to the open-source community (GitHub, Stack Overflow, blogging), • Existing exposure to Go or C++, Scala, AWS, Cassandra, Kafka, Elasticsearch..., • Prior experience in the cybersecurity or intelligence field, • Experience in thinking about, designing, or implementing programming languages and/or compilers, • Interesting hobbies #LI-SS1 Benefits of Working at CrowdStrike: Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at _ for further assistance. _ CrowdStrike participates in the E-Verify program. _ _ CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $160,000 - $250,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please _.

AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (Vision model (VLM) customization experience)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Full-Stack Software Engineer Type: Contract Compensation: $50–$80/hour Location: Remote Role Responsibilities • Write precise product specifications for application development and automatic grading., • Build complete reference implementations that meet all written criteria., • Author browser-driven acceptance criteria to verify user-visible behavior., • Calibrate task difficulty using frontier models to achieve target performance., • Verify tasks fail cleanly against empty repositories to ensure genuine feature development. Qualifications Must-Have • 3+ years of professional full-stack engineering experience., • Fluency in at least one modern frontend framework and one backend runtime., • Experience with auth, permissions, payment flows, and file upload in production., • Ability to specify systems precisely in writing., • Comfort with Docker, Git, and command-line tooling. Preferred • Experience building evaluations, benchmarks, or test suites for AI systems. Application Process (Takes 20–30 mins to complete) • Upload resume, • AI interview based on your resume, • Submit form Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome, • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Job DescriptionWe are looking for an experienced Sr. Software Engineer to support the design and enhancement of embedded software solutions for advanced voice and audio communication products in New York, New York. This Long-term Contract position focuses on building and maintaining Linux-based applications and platform capabilities for Intel x86 hardware, while contributing to modern user interface development and overall system performance. The ideal candidate brings a strong background in embedded Linux engineering along with hands-on experience across C#, .NET, React.js, JavaScript, and ASP.NET in a collaborative technology environment. Responsibilities: • Design, develop, and optimize embedded Linux software for communication devices that support voice and audio functionality., • Build and maintain platform components within Ubuntu Core and customized Linux distributions for Intel x86-based systems., • Create and refine user-facing application features for advanced interfaces, ensuring responsive performance and reliable operation., • Collaborate with cross-functional engineering teams to translate product goals into scalable software solutions., • Troubleshoot software issues across the stack, from operating system integration to application-level behavior., • Implement, test, and improve backend and frontend features using C#, .NET, ASP.NET, JavaScript, and React.js., • Participate in system customization, integration, and ongoing platform enhancements to meet technical and product requirements.• 5+ years of experience in embedded Linux software engineering., • Hands-on experience developing software for devices used in VoIP or audio communication environments., • Strong understanding of Linux platform development, including Ubuntu Core and customized embedded distributions., • Experience building software for Intel x86-based hardware environments., • Proficiency with C#, .NET, ASP.NET, JavaScript, and React.js., • Ability to develop, debug, and support both system-level and user interface components., • Strong problem-solving skills and the ability to work effectively within a collaborative engineering team.

Staff AI Engineer\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n ion. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description A major financial services company in NYC is growing its team rapidly, and they are looking for a Senior DevOps Engineer / Site Reliability Engineer who can join. If you’re passionate about high-availability, reliability, automation, we’d be excited to talk to you. Some technologies we are currently using: Linux, Docker, Terraform, Ansible, Java, Spring Boot, PostgreSQL, RabbitMQ, Keycloak, HAProxy, ELK Stack, InfluxDB, Telegraf, Grafana, Jenkins, Nexus, SonarQube, OpenVPN. Hope you’ll enjoy doing the following on a daily basis: • Documentation: Write specifications and documentation for the server-side features, • Development: Develop tools to help deploy and maintain our products., • Project planning: Share knowledge of possible configurations, risk, impact, and costs vs. benefits. Communicate operational requirements and development forecasts., • Testing: Test code, processes, and deployments to identify ways to streamline and minimize errors., • Deployment: Use configuration management software to automatically deploy updates and fixes into the production environment., • Maintenance and troubleshooting: Perform routine application maintenance to ensure the production environment runs smoothly. Develop maintenance requirements and procedures., • Performance management: Recommend performance enhancements by performing analysis, identifying alternative solutions, and assisting with modifications.Our team can get you up to speed if you have the fundamentals below:, • Have experience in Linux systems administration and understanding of how load balancers, web servers, databases, caching daemons, etc. work., • Have experience in shell scripting and one on more interpreted languages (ruby, python, Perl, etc), • Have excellent written and verbal communication skills., • Are pragmatic, iterative, and customer-driven., • Are organized, self-starting, and resourceful. You know how and when to ask for help., • Truly enjoy reduplicating work, automating processes, and improving the bus-factor whenever possible., • Are curious and desire to learn.

Job DescriptionElectrical Engineer, Analog & Mixed-Signal Location: NYC About Us Voyant Photonics is transforming machine perception with a new class of LiDAR devices that are compact enough to fit in the palm of your hand and powerful enough to measure range, velocity, and reflectivity with unparalleled accuracy. By leveraging cutting-edge silicon photonic chips smaller than your fingertip, we deliver sensors that are not only revolutionary in performance but also affordable enough to integrate into any system. Our technology disrupts the status quo of bulky, expensive, and power-hungry LiDAR systems, making high-precision sensing accessible for widespread adoption in robotics, autonomous vehicles, drones, industrial automation, and beyond. With Voyant, the next generation of machines can see, understand, and navigate the world like never before. Discover how we're redefining what's possible by making real products out of cutting-edge research in silicon photonics. The Opportunity We're looking for an early-career hardware engineer who wants to build real skills on a foundational technology, fast. You'll work alongside senior engineers on the analog and mixed-signal electronics behind our LiDAR modules — getting hands-on with schematic design, lab bring-up, and validation from day one, with direct mentorship and room to grow into greater ownership. Key Responsibilities Support analog and mixed-signal circuit design — TIAs, ADCs, precision current sources, and power supplies (LDOs, switching regulators) — under the guidance of senior engineers. Assist with schematic capture, component selection, and PCB layout coordination for hardware modules. Execute bring-up, characterization, and validation testing (EVT/DVT) against defined test plans, and document results clearly. Run signal integrity, power integrity, and basic EMI/EMC checks, with senior engineer review. Build hands-on proficiency with GHz-range oscilloscopes, VNAs, spectrum analyzers, and other precision lab equipment. Collaborate day-to-day with system architects, mechanical engineers, and firmware teams on integration tasks. Qualifications Experience: 0–3 years of hands-on hardware experience (internships, co-ops, and substantial academic or personal project work count). Education: BS or MS in Electrical Engineering or a related field. Technical Strengths: Solid grounding in analog and digital circuit design fundamentals. Comfort working in a lab environment and eagerness to build hands-on measurement skills. Tools & Skills: Exposure to schematic capture tools (e.g., Altium or similar) and basic SPICE simulation. Familiarity with fundamental test equipment (oscilloscopes, multimeters, power supplies). Preferred Qualifications Coursework or project experience in photonics, optics, or sensing systems. Exposure to PCB layout, FPGA/microcontroller integration, or Verilog/Verilog-AMS. Personal projects, competition teams (e.g., robotics, motorsports, CubeSat), or research involving analog or RF hardware. A demonstrated bias toward hands-on problem-solving and fast iteration in a startup environment. Benefits Package Competitive base salary and a meaningful equity package. Comprehensive health benefits (Medical, Dental, Vision). Unlimited PTO and paid company holidays. Team events and company meetups. Equal Opportunity Employer Voyant Photonics is an equal opportunity employer committed to building a diverse and inclusive workplace. We welcome applicants from all backgrounds and do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, pregnancy, marital or partnership status, age, national origin, citizenship, veteran or military status, disability, medical condition, genetic information, caregiver status, or any other characteristic protected by law.

Job DescriptionWhat you'll be part of Garner is on a mission to transform the U.S. healthcare system — and we're the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare "win win" — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role We are seeking an exceptional Staff Applied Researcher to join our Applied Science team. You will be responsible for building the algorithmic systems that power Garner — determining how we evaluate providers, make recommendations, and optimize for outcomes across cost, quality, and access. You will be responsible for turning ambiguous, real-world problems into systems that deliver measurable impact, defining the objective functions, metrics, and logic that drive our product. You will own these systems end-to-end, from problem definition through production and ongoing performance. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: • Own the most ambiguous, high-stakes problems facing the company end-to-end, and set how the team frames and approaches them, • Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks, • Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship, • Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for, and set the standard for how the team selects and applies these approaches, • Deliver algorithmic breakthroughs that move the company's most important metrics, pioneering approaches that become how applied science is done at Garner, • Review applied science work at the highest level across the company, ensuring the methods used across teams are sound and correctly applied, • Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: • Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions., • AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely., • Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. The ideal candidate has: • 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant advanced degree, PhDs preferred, • A bias toward action, quickly translating ideas into working prototypes to test approaches, • Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them, • Recognized technical authority, with the judgment to ensure the techniques used across an organization are sound, • Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem, • Strong communication skills, including at the executive level, with a track record of driving alignment across an organization, • A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedbackWhat you'll get here You'll work on problems that matter, at a company working to change healthcare at scale. You'll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you'll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It's demanding by design. You'll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use • Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment.Why this role This is a unique opportunity to work on high-impact search problems in healthcare, helping shape how members find better care through algorithmic systems that directly influence healthcare outcomes. Compensation Transparency: The target base comp range for this position is $260,000 – $382,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com. Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com.

Job Description Job Title AI QA Engineer Location Hybrid / Remote Employment Type Full-time Job Summary We are seeking an AI QA Engineer to ensure the quality, reliability, safety, and performance of AI-powered applications and machine learning solutions. The ideal candidate will design and execute testing strategies for AI systems, including large language model (LLM) applications, generative AI features, machine learning models, and AI-driven workflows. This role requires expertise in traditional software quality assurance combined with an understanding of AI model behavior, prompt engineering, and automated testing. Key Responsibilities • Design and implement test strategies for AI and machine learning applications., • Develop and maintain automated test frameworks for AI-powered systems., • Validate LLM responses for accuracy, consistency, relevance, and safety., • Create and manage test datasets, prompts, and evaluation benchmarks., • Test AI features for functionality, usability, performance, security, and reliability., • Identify, document, and track defects using bug management tools., • Perform regression, integration, API, end-to-end, and performance testing., • Evaluate AI systems for hallucinations, bias, toxicity, and prompt injection vulnerabilities., • Collaborate with AI engineers, data scientists, product managers, and developers to resolve issues., • Analyze model outputs and recommend improvements to prompts or workflows., • Monitor AI application performance after deployment., • Ensure compliance with organizational quality standards and AI governance policies. Required Qualifications, • Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field., • 3 5 years of experience in software quality assurance or test automation., • Experience testing web, mobile, or API-based applications., • Familiarity with AI, machine learning, or generative AI applications., • Strong understanding of software testing methodologies and QA best practices., • Experience with Agile or Scrum development environments. Preferred Qualifications, • Experience testing LLM-based or generative AI applications., • Knowledge of AI evaluation frameworks and benchmarking techniques., • Familiarity with prompt engineering and AI model behavior., • AI or cloud certifications (AWS, Microsoft Azure, Google Cloud, etc.)., • Experience with MLOps or AI deployment pipelines. Technical Skills, • Manual and automated testing, • Test case design and execution, • API testing (Postman, REST Assured), • Automation tools (Selenium, Playwright, Cypress), • Programming (Python, Java, JavaScript, or C#), • SQL and database validation, • Git and CI/CD pipelines, • Test management tools (Jira, TestRail, Zephyr), • Performance testing (JMeter, k6), • AI model evaluation techniques, • Prompt engineering, • LLM testing and validation, • AI safety testing (hallucinations, bias, toxicity, prompt injection), • Basic machine learning concepts, • JSON and REST APIs Soft Skills, • Analytical thinking, • Strong attention to detail, • Problem-solving, • Communication and documentation, • Collaboration with cross-functional teams, • Critical thinking, • Continuous learning, • Time management Preferred Experience, • AI-powered enterprise applications, • Generative AI products, • Machine learning platforms, • SaaS applications, • Conversational AI or chatbot testing, • Cloud-native applications Success Metrics, • Defect detection rate, • Test automation coverage, • AI response quality and accuracy, • Reduction in production defects, • Test execution efficiency, • AI safety and compliance metrics, • Release quality, • Customer satisfaction, • Mean time to detect (MTTD) and resolve (MTTR) issues Nice-to-Have Skills, • LangChain or similar AI orchestration frameworks, • AI evaluation frameworks (e.g., DeepEval, Ragas, LangSmith), • Vector databases, • Docker and Kubernetes, • MLOps tools, • Cloud platforms (AWS, Azure, Google Cloud), • Data annotation and synthetic data generation, • Security testing for AI systems, • Accessibility testing, • Experience with Retrieval-Augmented Generation (RAG) systems

Job DescriptionAbout Ajaia Ajaia is an AI implementation consultancy and product studio. We help organizations move from AI experimentation to measurable return on investment across four practices: AI Strategy and Advisory, Workforce Training and Enablement, Process Optimization, and Custom AI Development. Our work sits with executives and the people who do the work, and it is judged on whether something changed in production, not on whether a pilot looked good in a deck. Position Overview Ajaia is hiring a Product Manager to own products in Ajaia's product suite end to end. You will talk to users and customers every week, decide what gets built next and why, and say plainly what does not get built, including when the loudest voice in the room wants it. You will write specs an engineer can build from without a follow-up meeting, prototype with AI tools when a working demo settles an argument faster than a deck, and stay on the number after launch and act on what it tells you. This is a builder's seat: you will contribute to the code and the design yourself, not only direct them. Compensation: $100,000 to $175,000 base, plus a performance bonus of up to 100% of base salary. How we expect you to work AI use is a core execution requirement at Ajaia, not optional tooling. You will use AI daily to sort through usage data, draft specs, and build working prototypes yourself, and you are judged on what you keep from that output, not on how much of it you generated. The tools change fast, and staying current on what is worth using is part of the job. What you will do • Talk to users and customers every week. Not a quarterly survey. Real conversations, real usage., • Turn messy, sometimes contradictory signal, usage data, support tickets, sales requests, and what people say in interviews, into a ranked call on what gets built next., • Say plainly what does not get built, including a well-funded customer's request, when the evidence does not support it., • Write specs an engineer can build from without a follow-up meeting: the outcome, what is in and out of scope, where a human stays in the loop, and acceptance criteria someone could test., • Prototype the core flow yourself, wireframes, a clickable mock, or a working demo, when that settles the argument faster than a deck would., • Contribute to the code and the design directly: ship a small feature or fix with AI tools, mock the screen yourself, and hand engineers something running instead of something described., • Partner with the design team on what the solution should be and how it holds up for the people using it., • Partner with the delivery team and engineers on how the build runs and the date it ships by., • Present the roadmap and the tradeoffs to the people who fund it, including when a client or a salesperson is unhappy with the call., • Hold a priority decision under real pushback, or change it, and say why either way., • Ship it, then watch the number after launch and act on what it says. Requirements • Highly organized across multiple priorities and open questions at once., • Sharp judgment on what to build next, and clear about what not to build., • Strong plain writing: specs and decisions other people can act on without a follow-up meeting., • AI fluent: you use AI daily to sort signal, draft specs, and prototype, and you can tell good output from slop., • Comfortable contributing to code and design directly, with AI tools making you faster at both., • Comfortable holding a priority call under pushback, or changing it for stated reasons., • 1 or more years in product management, or work that proves the same skill., • On-site in New York., • A bachelor's degree is preferred and is not a requirement. Nice to have • Experience with a B2B product used by an operational or compliance function., • Comfort reading usage data or a support queue yourself., • Exposure to a regulated industry such as financial services, insurance, healthcare, or legal., • Prior experience in a 0-to-1 or early-stage product role. Benefits Competitive benefits.

Job Description Our client, a Financial company, is looking for a Lead Sitecore XM Cloud Engineer for their Jersey City, NJ location. Responsibilities: • We are seeking a strong, motivated Senior Software Engineer to lead the evolution of our digital platforms. In this role, you will champion the development, implementation, and maintenance of innovative, content-management-based software solutions. Your immediate focus will be driving a critical architectural shift: evaluating our current on-premises Sitecore XM custom setup, mapping out a migration strategy, and building an end-to-end Proof of Concept (PoC) in Sitecore XM Cloud., • Migration Strategy & Scoping: Identify migration scope and build a detailed list of tasks required to port custom, on-premises XM implementations to XM Cloud., • PoC Execution: Develop, deploy, test, and verify an end-to-end PoC that validates the new XM Cloud architecture., • Technical Documentation: Author comprehensive migration blueprints, including detailed architecture and design diagrams., • Collaborative Development: Work actively within an agile team to build and maintain high-performance CMS solutions. Requirements: • Sitecore Expertise: Deep, hands-on experience implementing Sitecore XM Cloud or leading migrations from on-premises XP/XM headless solutions to XM Cloud., • Proven ability to audit legacy custom CMS codebases and translate them into modern, cloud-native technical tasks., • Backend Development: Strong proficiency in C# and .NET architectures for handling legacy custom logic and integration endpoints., • Frontend Architecture: Modern web development mastery using Next.js and TypeScript within a decoupled, headless framework., • Preferred Qualifications, • Hosting & Rendering: Experience utilizing Vercel or managing on-premises Node.js servers for headless hosting within a Sitecore architecture., • Infrastructure Design: Background building or architecting high-availability (HA) setups to ensure maximum platform uptime., • Comments for Suppliers:, • We are looking for candidates with hands on experience in either working on XM cloud project currently or migrating on-premise XP/XM solution to XM cloud Why Should You Apply? • Health Benefits, • Referral Program, • Excellent growth and advancement opportunities

Job Description Firmware Engineer – Job Description (JD)Job Title Firmware Engineer Job Summary We are seeking a talented Firmware Engineer to design, develop, test, and maintain embedded firmware for microcontrollers, processors, and hardware devices. The ideal candidate should have strong expertise in embedded C/C , RTOS, device drivers, communication protocols, debugging tools, and hardware-software integration. The role involves developing reliable, high-performance firmware for embedded systems used in IoT, automotive, medical devices, consumer electronics, and industrial automation. Key Responsibilities • Design, develop, and maintain embedded firmware for hardware devices., • Develop firmware for microcontrollers (MCUs), SoCs, and embedded processors., • Write efficient, reliable, and maintainable code in C/C ., • Develop and integrate device drivers and hardware abstraction layers (HAL)., • Implement communication protocols such as UART, SPI, I2C, CAN, USB, and Ethernet., • Debug firmware using oscilloscopes, logic analyzers, and JTAG/SWD debuggers., • Optimize firmware for memory, power consumption, and performance., • Collaborate with hardware, software, QA, and manufacturing teams., • Perform unit testing, integration testing, and hardware validation., • Maintain technical documentation and firmware release notes., • Participate in code reviews and design discussions.Required SkillsEmbedded Programming, • Embedded C, • Embedded C, • Assembly Language (Basic), • Object-Oriented Programming (OOP), • Memory Management, • Interrupt Handling, • Bootloaders, • Linker ScriptsEmbedded Systems, • Microcontrollers (MCUs), • Microprocessors (MPUs), • System-on-Chip (SoC), • Embedded Linux, • Bare Metal Programming, • Real-Time Embedded SystemsRTOS (Real-Time Operating Systems), • FreeRTOS, • Zephyr RTOS, • ThreadX, • VxWorks, • QNX, • Embedded Linux RTMicrocontrollers Experience with one or more: • STM32, • NXP LPC, • Texas Instruments MSP430, • PIC Microcontrollers, • AVR, • ESP32, • Nordic nRF52, • Renesas, • Infineon, • ARM Cortex-M SeriesCommunication Protocols, • UART, • SPI, • I2C, • CAN, • CAN FD, • LIN, • USB, • Ethernet, • Modbus, • RS-232, • RS-485, • BLE, • Wi-Fi, • Zigbee, • MQTTDevice Drivers, • GPIO, • Timers, • PWM, • Client, • DAC, • DMA, • RTC, • Watchdog Timers, • Flash Memory, • EEPROMHardware Knowledge, • Digital Electronics, • Analog Electronics, • PCB Basics, • Schematics Reading, • Signal Processing, • Sensors & Actuators, • Power ManagementDebugging Tools, • JTAG, • SWD, • GDB, • OpenOCD, • Oscilloscope, • Logic Analyzer, • Multimeter, • Segger J-Link, • ST-LinkDevelopment Tools, • Keil MDK, • IAR Embedded Workbench, • STM32CubeIDE, • MPLAB X, • Eclipse, • VS Code, • CMake, • MakefilesVersion Control & CI/CD, • Git, • GitHub, • GitLab, • Jenkins, • Azure DevOpsTesting, • Unit Testing, • Integration Testing, • Hardware-in-the-Loop (HIL), • Firmware Validation, • Regression Testing

Job Description Senior Application Support & Development Engineer • Onsite Contract, NYC (upper West side) - ONSITE INTERVIEW REQUIRED We are seeking a seasoned application support and development engineer to help maintain, enhance, and modernize a diverse application portfolio spanning legacy systems, Microsoft technologies, SharePoint, Power Platform, and SQL Server. This role is ideal for someone who is comfortable owning production issues, extending existing systems with care, and using AI-assisted development practices responsibly to improve speed, quality, and documentation. What You'll Do • Triage and resolve production incidents across the application portfolio, ranging from legacy to modern technology stacks, with clear root-cause writeups and durable fixes., • Deliver enhancements and feature work against existing .NET, ASP.NET, and VB.NET codebases while preserving behavioral fidelity and improving maintainability., • Quickly learn the functionality, architecture, and design intent of existing systems in order to troubleshoot effectively and deliver changes that align with established patterns., • Build, maintain, and extend solutions across SharePoint Online, SharePoint on-premises, and the Microsoft Power Platform, with a strong focus on Power Apps and Power Automate., • Maintain and optimize SQL Server databases, including stored procedures, indexes, job schedules, performance diagnostics, and schema changes as code., • Partner with business analysts and client stakeholders to translate support requests and enhancement needs into well-scoped, testable change items., • Apply AI-assisted workflows to root-cause analysis, patch drafting, regression test generation, and runbook documentation, while following team standards for review and verification., • Own post-incident reviews and turn systemic findings into backlog items that reduce recurrence. What You Bring, • 8 years of professional software engineering experience, including meaningful production support ownership and real accountability during incidents., • Strong .NET, .NET Core, ASP.NET, C#, and VB.NET experience across Web Forms and MVC/Core applications., • Confidence reading, debugging, and extending legacy codebases without defaulting to unnecessary rewrites., • Ability to quickly understand existing system functionality, design, dependencies, and business workflows, then apply that knowledge to support, enhancement, and defect-resolution work., • Practical understanding of IIS hosting, application configuration, deployment considerations, and application lifecycle behavior., • Genuine comfort with VB.NET as a first-class requirement, including reading, debugging, and modifying existing code without friction., • Solid SQL Server and T-SQL depth, including stored procedures, triggers, complex queries, execution plan analysis, index strategy, concurrency and locking, and schema migration practices., • Hands-on SharePoint Online and/or SharePoint on-premises experience, including site and list administration., • Production delivery experience with Power Apps, including canvas and model-driven apps, and Power Automate flows., • A structured support mindset: disciplined incident triage, root-cause analysis, change management, testing, documentation, communication, and composure under production pressure., • Daily, beyond-autocomplete proficiency with GitHub Copilot agent mode or comparable AI-assisted development tools, applied to investigation, patch generation, test scaffolding, and runbook authorship., • Strong judgment in verifying AI-generated output before shipping code, documentation, or operational guidance. Nice to Have, • Azure DevOps experience covering boards, CI/CD pipelines, and repos in a real team delivery context., • Exposure to electric utility operations, IT/OT operations, or regulated-industry software environments., • Power BI familiarity., • Prior exposure to OpenROAD 4GL or Actian Ingres Database, even at a passing familiarity level., • Curiosity and composure when learning unfamiliar legacy stacks, tracing bugs through them, and delivering reliable fixes. Ideal Candidate Profile The ideal candidate is a pragmatic senior engineer who can move confidently between production support, enhancement delivery, and legacy system troubleshooting. They can quickly pick up the functionality, design, dependencies, and business context of existing systems, then use that understanding to make thoughtful changes without disrupting business-critical behavior. They value stability as much as speed, communicate clearly during incidents, and know how to improve maintainability without unnecessary rewrites. They are also comfortable using modern AI-assisted development tools as part of a disciplined engineering workflow, with strong review habits and accountability for final results. #tech #NoLinkedIn

Job DescriptionSoftware Engineer (GitHub Contributor) Role Type: Contractor Location: Remote – Worldwide Job Description We are seeking experienced Software Engineers to contribute to an AI training project focused on code generation, debugging, feature implementation, refactoring, and performance optimization. You'll create realistic coding challenges and reliable test environments to help train next-generation AI systems. Prior AI experience is not required. Required Skills • Python 3, Java, Rust, C++, or TypeScript, • Algorithms and Data Structures, • GitHub and Open-Source Contributions, • Bug Fixing and Feature Implementation, • Codebase Refactoring, • Performance Optimization, • Logical and Analytical Thinking, • Automated Testing and DebuggingScope of Work, • Develop realistic coding challenges for AI models., • Debug complex software issues and fix defects., • Implement and test new features., • Refactor and optimize existing codebases., • Build reproducible reinforcement learning environments with deterministic verifiers., • Provide reference solutions and document technical reasoning., • Review code submissions for accuracy, quality, and maintainability.Qualifications, • Strong programming experience in at least one supported language., • Experience with backend development, APIs, and scalable software systems., • Solid understanding of algorithms, data structures, and software engineering principles., • Proven ability to troubleshoot bugs and improve performance., • A GitHub profile showcasing relevant open-source contributions, or willingness to complete a technical assessment., • Strong analytical, problem-solving, and communication skills.Selection Process, • Submit your application and screening responses., • Complete an AI interview of approximately 20 minutes., • Complete a technical assessment if required., • Undergo hiring manager review.Start Timeline Selected candidates should be ready to begin within 24–48 hours of completing onboarding. Availability and weekly task submission requirements apply. Compensation Payment is output-based and depends on completed tasks meeting project specifications.

Job Description Title: Platform Database Engineer, Digital Infrastructure Location: New York City Position: Full Time Employment Job Description: The Platform Database Engineer is responsible for administration, development and scaling Outfront Media Digital Operations database systems. The engineer will support technical initiatives to implement data systems for digital content delivery and digital boards’ uptime analyses. The engineer will work on ensuring timely data collection and the collected data is within required quality standards The engineer will also support all database related operations like backup, upgrade, performance tuning, recovery and failover. The engineer will be on call for 24x7 production issues.. Core Responsibilities: • Design, administer, tune, and monitor production databases ensuring 24x7 operations and good performance;, • Collect, analyze and share data to help operations and business teams drive improvement in key business metrics;, • Utilize database and web application technologies to evaluate and develop innovative business intelligence tools and automated reports;, • Design, develop and test BI solutions such as databases, data warehouse, queries, views, reports, and dashboards;, • Assist in data conversions, imports and exports of data within and between internal and external systems;, • Manage and support development and staging database environments;, • Implement and improve backup/recovery processes, disaster recovery and failover processes;, • Troubleshoot BI tools, database systems, and overall performance;, • Interact with Business, Program Management, and Engineering on meeting ongoing reporting requirements;, • Document new and existing models, solutions and implementations;, • Strictly adhere to process, instructions, policies, and standards Requirements:, • BS in Computer Science or information systems related field or equivalent experience, • 5+ years of operational PostgreSQL and MySQL database skills in a Linux production environment, • 3+ years of experience supporting fast growing mission critical production systems, • Knowledge of business intelligence tools and systems, • Data analysis and data mining skills, • Good Linux and shell scripting skills (PHP, Python, LAMP), • Self-starter and independent worker, • Good verbal and written communications skills, • Good documentation skills, • Experience with enterprise data warehouses a plus, • MySQL/PostgreSQL Management Certifications highly desired, • Ability to create clear step by step knowledge base documents for NOC and field personnel to follow and resolve known issues, • Participate in 24x7 on call rotations

Job DescriptionPay Rate Range: $ 45.45 - 49.24/hr. Role Name - AI Enabled SDET Job Description: What We are Looking for (Must-Have) Core Engineering -Should have 5-8 years of experience -Expert-level Java and/or Python (OOP, Data Structures, Design Patterns) -Proven experience building automation frameworks from scratch -Hands-on Playwright expertise for modern UI automation -Strong API & integration testing (REST, microservices) -CI/CD experience with automated quality gates (TeamCity, Jenkins, GitHub) -Solid understanding & proficiency with SQL, handling backend stores and performing data validation -Experience validating high-availability, low-latency systems -Practical, maintainable BDD implementations. Technical Skills: Java, Python, GenAI, Prompt Engineering, Playwright, API Testing, Microservices Testing, SQL, CI/CD, Jenkins, GitHub Actions, Test Automation Frameworks, Observability (Logs/Metrics/Traces), AI Evaluation Frameworks, MCP, AI Agents, Spec-Driven Development, Quality Engineering, SDET. Roles & Responsibilities About the Role: The organization is building an Engineering-First Quality Engineering (QE) team focused on developer-grade automation, system reliability and production excellence across mission-critical platforms This is not a traditional QA role. We hire developers who engineer quality, not testers who execute scripts. The candidate is expected to design and build scalable quality engineering solutions, partner deeply with developers and architects, and ensure quality is designed in, automated, observable, and enforced across SDLC. Key Responsibilities Quality Engineering & Automation -Build scalable automation frameworks from scratch across UI, API, integration & event-driven layers -Act as a Quality Architect influencing system design, testability & release readiness -Embed automated quality gates into CI/CD pipelines. -Engineer quality for Microservices, Distributed systems and High-availability platforms -Leverage AI / GenAI to accelerate Test design, automation, development, evaluation and debugging -Practice Spec-Driven Development (SDD) to align specifications, implementation, and validation -Own end-to-end production quality, including release certification and incident triage. Reliability & Distributed Systems -Strong understanding of microservices and event driven architectures. -Experience with performance, load, stress, and resilience testing. -Ability to debug using logs, metrics, and traces. -Using production telemetry to guide quality strategy. AI-Driven & Spec-Driven Engineering (Must-Have) -Hands-on use of AI/GenAI tools for test design, automation, coding, and debugging. -Strong AI evaluation skills, including validating AI-generated code and tests. -Expertise in prompt engineering and context management. -Proven experience with spec-driven development (SDD). -Experience using and developing agents, skills, and Model Context Protocol (MCP) integrations. -Ability to safely embed AI-assisted QE workflows into CI/CD pipelines. -Strong understanding of responsible AI usage and verification of AI-generated outputs. Quality Ownership -Experience with release certification, regression strategy, and production validation. -Hands-on experience with incident triage and root cause analysis. -Willingness to support production releases, including on-call rotations. Skills:CategoryNameRequiredImportanceExperienceSkillCategoryTest1_MNDigital : Application Programming Interface (API)Yes14-7 years

Job Description Senior / Staff Member of Technical Staff Employment Type: Full-time Experience: 4+ years Focus: AI Product Engineering, Full-Stack Development, Distributed Systems, APIs, Customer Research Platforms About Our Client Our client is building an AI-native customer research platform that transforms how companies understand their customers and make business decisions. Their AI agents automate the entire research process, from designing studies and recruiting participants to conducting interviews and synthesizing insights. The platform connects companies with a network of more than 50 million research participants, supports interviews in over 120 languages, and helps organizations gather insights at unprecedented speed and scale. The company is also developing AI-powered digital twins that simulate real customer behavior, enabling businesses to test products, messaging, and strategic decisions before bringing them to market. Trusted by major technology companies, including Microsoft and Anthropic, the platform is designed to fundamentally change how customer research is conducted. The company has announced an agreement to be acquired by a major publicly traded enterprise software company, creating an opportunity for engineers to build AI-native products with the speed of a startup and the potential distribution of a global technology leader. About the Role Our client is hiring a Senior / Staff Member of Technical Staff to build and scale its AI-powered customer research platform. This is a high-ownership engineering role that combines full-stack product development, AI-powered features, platform engineering, and user experience. You'll work across the product, from building conversational AI experiences and research insights to developing participant recruitment systems, improving platform design, and scaling backend infrastructure. The ideal candidate is a product-minded software engineer who enjoys building customer-facing applications, solving complex technical problems, and owning features from concept through production. What You'll Do Build and ship AI-native product features across the customer research platform. Develop conversational AI capabilities that allow customers to interact with research findings and insights. Build analysis and insights tools that help businesses understand customer feedback and make decisions. Develop participant recruitment, incentive management, and self-service research workflows. Build systems for managing research panels, participant lists, and recruitment at scale. Improve the overall product experience, including frontend architecture, UI components, and design systems. Partner closely with product and design teams to develop intuitive, customer-facing experiences. Design and build scalable APIs, backend services, and distributed systems. Own features end-to-end, from technical design and implementation through deployment and iteration. Help expand the product roadmap and improve the platform as customer adoption grows. What We're Looking For 4+ years of professional software engineering experience, with demonstrated senior-level technical ability. Strong full-stack software engineering fundamentals. Experience building and shipping production software used by real customers. Strong product instincts and ability to translate ambiguous requirements into intuitive user experiences. Experience developing backend APIs, services, and scalable application architecture. Comfortable collaborating with product managers, designers, and engineers. Ability to take ownership of complex technical problems from design through deployment. Experience working with modern frontend frameworks and backend technologies. Strong understanding of system design, software architecture, and engineering best practices. Ability to move quickly, solve problems independently, and thrive in a high-performance engineering environment. Bonus Experience Experience building AI-native products or LLM-powered applications. Experience with conversational AI, agentic workflows, or AI-driven analytics. Experience building data analysis, insights, or business intelligence products. Experience developing self-service platforms, marketplaces, or participant recruitment systems. Experience with distributed systems and high-scale backend infrastructure. Experience building frontend design systems or complex interactive interfaces. Previous experience at an early-stage or high-growth startup. Why This Opportunity Build AI agents that automate customer research from start to finish. Work on products used by some of the world's most recognized technology companies. Join a small, highly technical team building an AI-native platform. Own meaningful product features across frontend, backend, and AI systems. Help develop new ways for companies to understand customers through AI-powered research. Experience startup-style engineering with the potential reach and resources of a global enterprise software company. Help shape a platform positioned to serve a significantly larger enterprise customer base. Ideal Candidate Profile The ideal candidate is a senior or staff-level, product-minded full-stack engineer who enjoys building sophisticated customer-facing software. They have strong engineering fundamentals, care about product quality and user experience, and can move comfortably between frontend features, backend systems, and AI-powered functionality. This person thrives in an environment where engineers take ownership, work closely with product and design, and ship meaningful features without unnecessary process.

Job DescriptionGenesis10 is seeking a DevOps Engineer for a contract position with a financial services client located in New York, NY. This is a hybrid position and requires being onsite 3 days per week. Summary: We are seeking a DevOps Engineer with hands-on, production-level experience designing, securing, and operating enterprise CI/CD pipelines for modern cloud-based applications. This role requires far more than GitLab source control experience—you will own automated software delivery pipelines, implement governance and security best practices, and enable reliable deployments across multiple application stacks and cloud environments. The ideal candidate has a strong background in GitLab CI/CD, cloud-native application deployments, container technologies, Azure, DevSecOps, and infrastructure automation, with experience supporting enterprise software delivery at scale. Key Responsibilities: GitLab CI/CD Engineering • Design, build, maintain, and troubleshoot multi-stage GitLab CI/CD pipelines using .gitlab-ci.yml, • Configure and manage GitLab runners, artifacts, caching, CI/CD variables, deployment environments, approvals, and deployment gates., • Develop reusable pipeline templates, shared components, include files, and parent/child pipelines to standardize delivery across teams., • Implement GitLab governance, including branching strategies, merge request workflows, CODEOWNERS, protected branches/tags, merge trains, and approval rules., • Monitor and optimize pipeline performance, reliability, observability, and maintainability., • Integrate automated testing, security scanning, dependency scanning, secret detection, container scanning, and policy-based quality gates into delivery pipelines.Application Build & Deployment, • Build, test, package, and deploy enterprise applications across one or more of the following technology stacks:, • .NET / C#, • Java, • Python, • Node.js / JavaScript / TypeScript, • Candidates should understand the unique CI/CD requirements of each platform, including dependency management, build optimization, testing frameworks, artifact creation, security scanning, containerization, and deployment strategies.Cloud & Container Deployment, • Deploy and manage containerized applications through GitLab CI/CD into Azure-based environments., • Build, tag, scan, and publish Docker container images using Azure Container Registry (ACR) or comparable cloud registries., • Configure deployment workflows across Development, Test, UAT, and Production environments with approvals, promotions, rollback strategies, and health validation., • Manage Docker images, networking, runtime configuration, logging, monitoring, and release processes., • Integrate Infrastructure-as-Code solutions such as Terraform, Bicep, ARM Templates, or CloudFormation into CI/CD pipelines.Azure & AWS Cloud Technologies, • Support cloud-native deployments using foundational Azure and AWS services., • Azure, • Azure Container Registry (ACR), • Azure Key Vault, • Microsoft Entra ID, • Azure RBAC, • Azure Storage, • Azure Monitor, • Virtual Networks, • Resource Groups, • Service Principals and Managed IdentitiesAWS, • EC2, • IAM, • VPC, • S3, • CloudWatch, • ECR, • ECS, • Amazon Machine Images (AMIs) / Golden ImagesSecrets Management & Identity, • Integrate Azure Key Vault into CI/CD workflows for secure management of secrets, certificates, API keys, and connection strings., • Implement secure credential management using masked GitLab variables, environment isolation, least-privilege access, and credential rotation., • Configure GitLab authentication to Azure using Service Principals, Microsoft Entra ID, Azure RBAC, and secure identity practices., • Experience with Workload Identity Federation/OpenID Connect (OIDC) is a plus.AI-Assisted Engineering, • Utilize AI-assisted development tools such as Claude Code or comparable solutions to improve development, testing, documentation, debugging, and code quality., • Ensure AI tools are used responsibly within enterprise governance standards while maintaining human oversight, secure coding practices, and protection of proprietary code and sensitive information.DevSecOps & Enterprise Governance, • Support enterprise release governance, auditability, access controls, and separation-of-duties requirements., • Collaborate with software engineering, cloud infrastructure, platform engineering, and security teams to establish scalable CI/CD standards and improve developer productivity., • Champion DevSecOps best practices across the software development lifecycle. Required Qualifications: • 5+ years of experience designing and supporting enterprise CI/CD pipelines., • Strong hands-on experience with GitLab CI/CD in production environments., • Experience creating reusable GitLab pipeline templates and deployment automation., • Experience deploying containerized applications using Docker and Azure container services., • Strong knowledge of Azure cloud services, identity, networking, monitoring, and security., • Working knowledge of AWS cloud services and container deployment concepts., • Experience integrating Infrastructure-as-Code into CI/CD pipelines., • Solid understanding of DevSecOps principles, automated testing, and application security., • Experience implementing secure secrets management and identity integration., • Strong troubleshooting, automation, and scripting skills., • Excellent communication and collaboration skills. Preferred Qualifications: • Experience supporting enterprise financial services or other highly regulated environments., • Experience with Azure Kubernetes Service (AKS), Kubernetes, or other container orchestration platforms., • Experience with Terraform, Bicep, ARM Templates, or CloudFormation., • Familiarity with OpenID Connect (OIDC) and Workload Identity Federation., • Experience using AI-assisted developer tools such as Claude Code, GitHub Copilot, or similar enterprise AI coding platforms., • Experience driving CI/CD standardization and platform engineering initiatives across multiple development teams. The pay rate range for this position is $70 - $90 per hour If you have the described qualifications and are interested in this exciting opportunity, apply today! Genesis10 Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: • Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years., • The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years., • Access to an experienced, caring recruiting team (more than 7 years of experience, on average.), • Behavioral Health Platform, • Medical, Dental, Vision, • Health Savings Account, • Voluntary Hospital Indemnity (Critical Illness & Accident), • Voluntary Term Life Insurance, • 401K, • Sick Pay (for applicable states/municipalities), • Commuter Benefits (Dallas, NYC, SF), • Remote opportunities available For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. #LI-EA1 #DIG10-NY

Job Description Let’s be unstoppable together! Circana is a leading provider of technology, AI, and data solutions for consumer packaged goods companies, manufacturers, and retailers. Our predictive analytics and Liquid Data® platform help clients measure market share, uncover consumer behavior, and drive growth—powered by six decades of expertise and an expansive, high-quality data set. At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We’re a global company dedicated to fostering inclusivity and belonging. We value and celebrate the unique experiences, cultures, and viewpoints that each individual brings. By embracing a wide range of backgrounds, skills, expertise, and beyond, we create a stronger, more innovative environment for our employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana. Learn more at www.circana.com. Role Overview Circana is building an agentic ecosystem on the industry's richest view of consumer behavior: intelligent systems that reason, plan, and act across the data the world's largest brands and retailers run on. This is a Forward Deployed Engineer (FDE) role. FDEs embed with the teams who run Circana's business, in operations, client service and product, and turn what those teams know into working software: AI agents where judgment is needed, automations where a rule is enough, and the MCP servers and integrations that let both reach our systems. You will work in a small pod with a principal engineer and domain experts, build on Circana's agent platform and tooling, and own whether the result works in production. FDEs move between engagements: embedded builds with a business team, shared platform components, and client-facing solutions. Job Responsibilities • Embed with domain experts and the engineers who own the underlying systems. Learn how the work really happens, including the exceptions, and resolve ambiguity at the source., • Decide, step by step, whether the work calls for a deterministic automation, an agent, or a person, and build whichever it is., • Build agents end to end: tools, MCP servers, context and prompt design, plan construction, tool result shaping, and guardrails., • Build integrations into real enterprise systems, including ones with thin documentation or no API: REST services, databases, file-based feeds, and schedulers., • Build and maintain the evaluation sets, graders and regression suites that measure whether a solution is right against ground truth; investigate failures down to the step that caused them., • Debug from traces: reproduce, isolate, fix, and add the test that prevents recurrence., • Automate the development loop itself: turn repeated manual work into commands, hooks, and subagents., • Move decisions forward with working prototypes. Requirements • A track record of shipping production software that real users depended on, including AI or agentic systems., • Strong integration engineering: APIs, data pipelines, databases, and systems you did not build., • Deep practical craft with models: context management, prompting, structured outputs, and tool design., • Strong Python; productive in an unfamiliar codebase quickly., • Fluent daily use of agentic coding tools; Claude Code preferred., • Comfortable working directly with non-technical experts, and persistent in getting to how a process actually works., • Experience running workloads on a major cloud platform; ours can be learned quickly., • Clear written communication under time pressure., • Demonstrated self-direction: work you initiated, built, or fixed without being asked. Preferred • Prior forward deployed, solutions, or field engineering experience., • Agentic systems in production, across multiple model families., • Hands-on experience with an agent orchestration framework (Google ADK, LangGraph, Microsoft Agent Framework, Claude Agent SDK, or similar) on GCP Vertex AI, Azure AI Foundry, or a comparable AI stack., • Working TypeScript and solid SQL., • Front end capability: React, TypeScript, CopilotKit or similar., • Workflow orchestration (Airflow or similar) and large transactional datasets., • Evaluation and observability tooling; contributions to agent frameworks or MCP servers. Tech Stack & Tools Experience with any of the platforms and frameworks below is relevant; skills transfer readily between them. • Platforms: GCP Vertex AI, Azure AI Foundry, on-prem, • Orchestration: Google ADK, LangGraph, Microsoft Agent Framework, Claude Agent SDK, • Models: Anthropic, Google, OpenAI, open-weight families, • Protocols: MCP, A2A, OpenAPI, OAuth 2.0, • Engineering: Python, TypeScript, SQL, Claude Code, • Delivery: evaluation harnesses as CI, tracing and observability tooling, CI/CD integration Circana Behaviors Beyond technical skills, experience, and role-specific attributes, these shared behaviors are fundamental to our culture and success. We seek individuals who consistently demonstrate and champion these behaviors in their daily work: • Stay Curious: Being hungry to learn and grow, always asking the big questions., • Seek Clarity: Embracing complexity to create clarity and inspire action., • Own the Outcome: Being accountable for decisions and taking ownership of our choices., • Center on the Client: Relentlessly adding value for our customers., • Be a Challenger: Never complacent, always striving for continuous improvement., • Champion Inclusivity: Fostering trust in relationships engaging with empathy, respect, and integrity., • Commit to each other: Contributing to making Circana a great place to work for everyone. Location: This position can be located in the following area(s): Chicago, IL (Hybrid) or NYC, NY (Hybrid) The below range reflects the range of possible compensation for this role at the time of this posting. We may ultimately pay more or less than the posted range. This range may be modified in the future. An employee’s position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue-based metrics, any collective bargaining agreements, and business or organizational needs. The salary range for this role is $160,000 USD to $200,000 USD. This job is also eligible for bonus pay. We offer a comprehensive package of benefits including paid time off, medical/dental/vision insurance and 401(k) to eligible employees. An offer of employment may be conditional upon successful completion of a background check in accordance with local legislation and our candidate privacy notice. Your current employer will not be contacted without your permission. You can apply for this role through the Circana careers website or Intranet site for internal candidates. This role is subject to AI-assisted screening. Circana uses artificial intelligence (AI) to assess resumes for alignment with job requirements by helping locate details in resumes that relate to the job description. This position is expected to remain open for approximately 30 days and may close earlier if sufficient qualified candidates are identified.

Job DescriptionYears of Experience • 10 years of relevant experience in designing, architecting, and implementing PAM and EPM solutions across complex enterprise environments.General Description, • Serve as the subject matter expert for Privileged Access Management (PAM), providing architecture guidance and best practices across CyberArk platforms., • Partner with business, security, infrastructure, and application teams to assess privileged access risks, define PAM roadmaps, and deliver secure, scalable solutions aligned with organizational objectives., • Evaluate existing PAM and identity security environments, recommend modernization and optimization strategies, and drive adoption of industry-leading privileged access controls., • Lead client-facing discussions, workshops, and design reviews with US-based stakeholders, translating business and compliance requirements into effective PAM solutions., • Provide governance, operational oversight, and lifecycle management for PAM platforms, including continuous improvement, upgrade planning, troubleshooting, documentation, and adherence to security and regulatory standards.Technical Requirements, • Creating and implementing strategies for managing privileged access using CyberArk, designing PAM solutions, and ensuring the secure storage, management, and retrieval of sensitive credentials in enterprise environments., • Developing and enforcing security policies, access controls, and privileged access management procedures using CyberArk capabilities to mitigate security risks and support compliance requirements., • Design secure and scalable CyberArk PAM solutions, creating High-Level Designs (HLDs) and Low-Level Designs (LLDs) for cloud, on-premises, and hybrid environments while working closely with US-based stakeholders., • Implement, oversee, and document high-level and low-level designs for CyberArk deployments, defining PAM strategies aligned with business, security, and regulatory requirements., • Collaborate with automation SPOCs, application teams, and onsite stakeholders to build, test, and optimize PAM-related automation solutions., • Design, deploy, and support high-performance, highly available CyberArk PAM environments with large-scale target endpoints, creating workflows, custom connectors, policies, and integrations., • Should be capable of deploying, installing, and configuring CyberArk components (Vault, CPM, PVWA, PSM, PSMP, AIM/CCP) as per client requirements., • Develop custom plugins, integrations, and connectors for CyberArk CPM/PSM Password Safe/PRA components, as required., • Hands-on experience or knowledge in configuring CyberArk PTA, Endpoint Privilege Management (EPM) and privileged access monitoring capabilities., • Integrating various platforms with CyberArk, including Windows, UNIX/Linux, databases, network devices, SSH keys, cloud platforms, SAP, and enterprise applications., • Creating and managing Safes, platforms, owners, vault policies, asset groups, account management policies, and access controls within CyberArk environments., • Should be familiar with CyberArk Password Upload Utility, PACLI, REST APIs, and corresponding administration, onboarding, and integration utilities/tools., • Experience in integrating CyberArk solutions with LDAP/Active Directory, SIEM, SNMP, MFA, and other identity and access management systems., • Strong scripting skills using PowerShell, Python, Shell scripting, or APIs to automate tasks, develop integrations, and customize CyberArk solutions., • Knowledge of regulatory requirements and industry standards related to privileged access management, including NIST, CIS, SOX, PCI-DSS, HIPAA, and GDPR., • Experience with security monitoring tools and integrating CyberArk with Security Information and Event Management (SIEM) platforms; ability to support client workshops, design discussions, and solution reviews in an onsite US-facing environment.Soft Skills, • Excellent Verbal and written communication skills in English., • Ability to present solutions to clients in person and remotely if needed., • Good documentation skills that will enable creation of design documents for the technical solutions proposed., • Excellent problem-solving skills., • Good collaboration skills in working with virtual and distributed teams.Certifications, • Good to have relevant PAM certifications such as:, • CyberArk Certified Delivery Engineer (CDE), • CyberArk Certified Defender (CCD), • CyberArk Certified Sentry (CCS), • CyberArk Certified Client (CCG), • CISSP (Certified Information Systems Security Professional), • Educational Qualifications, • University degree in IT or/and IT Security

Job Description Senior Software Engineer Location: United States Employment Type: Full-time Experience: 3–10 years Focus: Backend Engineering, AI-Native Products, Fintech, Mortgage Servicing Infrastructure About Our Client Our client is building an AI-native operating system for mortgage servicing. The mortgage industry moves billions of dollars through highly complex, regulated workflows across federal, state, and agency requirements. Our client is modernizing this infrastructure with software that helps enterprise customers manage critical mortgage servicing operations with more speed, accuracy, and intelligence. The company is growing quickly, has recently signed multiple large enterprise customers, and is expanding its engineering team to support continued product and platform scale. About the Role Our client is hiring a Senior Software Engineer to build and scale backend systems that power mission-critical mortgage servicing workflows. This is a high-ownership role for an engineer who can own features end-to-end, operate with autonomy, and meet a strong technical bar. You'll work across product, backend, platform, and infrastructure problems depending on team fit and business priorities. The team is AI-native in how they build. Engineers are expected to use AI-assisted development tools to move faster while maintaining strong engineering judgment, human review, and production-quality standards. What You'll Do • Own product and platform features end-to-end in a fast-moving startup environment, • Build and scale backend systems that support billions of dollars in mortgage transactions, • Design reliable infrastructure for complex financial, regulatory, and operational workflows, • Build systems that support federal, state, and agency compliance requirements, • Use AI-assisted development tools to write, test, and ship production code, • Partner across product, platform, infrastructure, and engineering teams, • Break down ambiguous technical problems and turn them into shipped outcomes, • Improve system reliability, scalability, performance, and maintainability, • Help define engineering standards as the company scales with large enterprise customers What We're Looking For • 3–10 years of professional software engineering experience, • Strong backend engineering fundamentals, • Experience building and scaling production systems, • Ability to own features from design through implementation, launch, and iteration, • Strong technical judgment and ability to pass a high engineering bar, • Comfort operating with autonomy in a startup environment, • Experience working with complex business logic, regulated workflows, or high-stakes systems, • Comfort using AI tools as part of the software development workflow, • Strong communication skills and ability to collaborate across product and engineering teams, • Bias toward shipping reliable, maintainable software Bonus Experience • Experience in fintech, mortgage technology, lending, servicing, banking, insurance, or other regulated industries, • Experience building backend systems that handle payments, transactions, compliance workflows, or financial operations, • Experience with platform or infrastructure engineering, • Experience at a high-growth startup or enterprise SaaS company, • Experience using AI-assisted development tools in production engineering workflows Why This Opportunity • Join a rapidly growing company building modern infrastructure for mortgage servicing, • Work on systems that support billions of dollars in financial transactions, • Build AI-native software for a large, highly regulated industry, • Partner with strong engineers solving complex backend, product, and infrastructure problems, • Own meaningful features end-to-end with high autonomy, • Join at a stage where large enterprise customer demand is creating major engineering opportunities, • Help shape the technical foundation of a category-defining platform

Job Description Job Title AI Evaluation Engineer Location Hybrid / Remote Employment Type Full-time Job Summary We are seeking an AI Evaluation Engineer to design, implement, and maintain evaluation frameworks for AI and machine learning systems, with a focus on Large Language Models (LLMs) and generative AI applications. The ideal candidate will develop robust evaluation methodologies, assess model performance across quality and safety dimensions, and collaborate with AI engineers, data scientists, and product teams to improve AI system reliability and user experience. Key Responsibilities • Design and implement evaluation frameworks for AI, machine learning, and generative AI systems., • Develop automated and manual evaluation pipelines to assess model quality and performance., • Define evaluation metrics for accuracy, relevance, factuality, consistency, completeness, latency, and user satisfaction., • Create benchmark datasets, test suites, and evaluation scenarios for AI models., • Evaluate LLMs and AI applications for hallucinations, bias, toxicity, fairness, robustness, and safety., • Measure Retrieval-Augmented Generation (RAG) performance, including retrieval quality and response grounding., • Conduct A/B testing and comparative evaluations of models, prompts, and AI workflows., • Analyze evaluation results and provide actionable recommendations for model improvement., • Collaborate with AI engineers, data scientists, product managers, and QA teams throughout the AI development lifecycle., • Monitor production AI systems and identify performance degradation, data drift, and model drift., • Document evaluation methodologies, findings, and best practices., • Ensure compliance with organizational AI governance, privacy, security, and responsible AI policies. Required Qualifications, • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Software Engineering, or a related field., • 3 5 years of experience in AI, machine learning, software engineering, data science, or model evaluation., • Strong understanding of machine learning concepts and evaluation methodologies., • Experience evaluating AI or generative AI applications., • Proficiency in Python and SQL., • Experience with REST APIs and cloud-based applications. Preferred Qualifications, • Master's degree in AI, Machine Learning, Data Science, Computer Science, or a related field., • Experience evaluating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems., • Knowledge of Responsible AI, AI safety, and AI governance principles., • Experience with MLOps and model lifecycle management., • AI or cloud certifications (AWS, Azure, Google Cloud). Technical Skills, • Python, • SQL, • Machine learning fundamentals, • LLM evaluation methodologies, • Prompt engineering, • RAG evaluation, • AI benchmarking techniques, • Statistical analysis, • Data visualization (Power BI, Tableau, Matplotlib), • Git and CI/CD, • REST APIs, • JSON, • AI evaluation frameworks (DeepEval, Ragas, LangSmith, Promptfoo), • MLflow, • Docker and Kubernetes, • Cloud platforms (AWS, Azure, Google Cloud) Soft Skills, • Analytical thinking, • Critical thinking, • Problem-solving, • Strong communication skills, • Technical documentation, • Collaboration, • Attention to detail, • Time management, • Continuous learning Preferred Experience, • Generative AI applications, • Conversational AI and chatbots, • Enterprise AI platforms, • Retrieval-Augmented Generation (RAG), • Machine learning model validation, • AI-powered SaaS applications, • Regulated industries such as healthcare, finance, or insurance Success Metrics, • AI evaluation coverage, • Benchmark quality and completeness, • Improvement in model accuracy and reliability, • Reduction in hallucinations and unsafe responses, • Evaluation pipeline automation, • Detection of model regressions before release, • Production AI performance and stability, • Stakeholder satisfaction, • Compliance with Responsible AI and governance standards Nice-to-Have Skills, • Explainable AI (XAI), • Model monitoring and observability tools, • Synthetic data generation, • Vector databases, • LangChain or similar AI orchestration frameworks, • Data annotation tools, • Experiment tracking platforms, • A/B testing methodologies, • AI red teaming, • Familiarity with standards such as NIST AI Risk Management Framework (AI RMF) or ISO/IEC 42001

Job Description As an engineer at Bask you will work directly with the CEO and CTO to build and design the software infrastructure that will serve as the backbone of telehealth. We are looking to expand our software engineers, seeking those with deep rooted entrepreneurial spirit. Our serverless platform is a multi-tenant monorepo — Next.js and React on the front, tRPC and Prisma behind it, deployed on SST, TypeScript throughout. One engineer can follow a change from a form field to the database without crossing a team boundary. That's the point. Engineering at Bask Health is AI-first and builder-led. Work starts with general understanding of problem, moves to tools like Claude and Cursor for further investigation, making a plan and building, tested on staging with realistic data, released to production, tested with real patient and care teams, and then back for systems and polish. AI is a default part of how we work, not a side experiment — because moving fast in healthcare requires every advantage. We are looking for engineers who take end-to-end ownership, treat AI as a real collaborator, and care deeply about building software that meaningfully improves how healthcare is delivered. What You'll Do • Design, build, and ship high-quality product experiences. Own key surfaces end to end, from concept through production. Write elegant, well-tested code — we have a real test suite and we intend to keep it that way., • Work across the stack. Follow a feature from the interface through the API to the database. No handoffs, no waiting on another team., • Work AI-first with Cursor and Claude Code. Use LLMs as your starting point. Draft intent, explore implementations, scaffold components, and refactor with AI in the loop. Apply your own judgment to meet the quality bar healthcare demands., • Prototype fast and validate with real users. Build and test quickly with real patients and care teams. Use what you learn to refine before fully committing — especially in sensitive clinical contexts where getting it right matters., • Build for scale and own the codebase. Translate product needs into reusable, well-architected patterns that make the next feature faster to ship., • Make automation legible and trustworthy. Build systems that clearly communicate what AI and automation are doing on behalf of patients and providers. Earn trust through transparency, reliability, and thoughtful defaults., • Champion performance, accessibility, and reliability. Ship work that is fast, robust, and accessible. Partner across the team to debug, optimize, and raise the bar over time., • Share AI-native workflows. Document prompts, patterns, and workflows that work, so we move faster together without cutting corners that matter to patient outcomes. We are a highly collaborative team. Requirements Requirements A full-stack generalist who has taken a product from 0 to 1 and can apply that instinct inside a system that already has real patients on it. Entrepreneurial, willing to roll up their sleeves, and drawn to a mission that disrupts how healthcare gets delivered. • 5+ Years of experience, • You are dangerous on the frontend of the stack., • You are a highly skilled dev (React, TypeScript, Next.js, Tailwind and JavaScript)., • You also have backend skills (tRPC, Drizzle ORM, SQL, Node, SST)., • You can work independently and are comfortable owning entire projects or large areas of the codebase., • Strong experience building paid products and services is preferred., • React Native or Expo experience is a plus., • You are a strong communicator, able to clearly articulate technical problems, constraints, and timelines., • You are comfortable working in a fast-paced, unstructured, startup environment.

Job DescriptionAI Software Engineer NYC AI Labs – Investment Management J Harlan Group is currently conducting a search for an AI Software Engineer to join the firm's AI Engineering team at a prominent global Investment Manager. This opportunity offers the opportunity to collaborate with talented engineers, product owners, and business partners building high-impact AI products with leverage across the firm. As a Software Engineer on T. Rowe Price Labs' AI Engineering team, you will design, develop, test, and deploy AI agents and intelligent systems, helping move innovative ideas from concept toward enterprise scale. Working in a Build-Operate-Transfer model, you will contribute to incubating new AI products, help harden them for production, and partner with business-aligned technology teams to scale responsible AI solutions across the enterprise. This is a hands-on, end-to-end engineering opportunity with direct responsibility for building modern AI-enabled systems as part of T. Rowe Price Labs' AI Engineering team. You will collaborate in cross-functional squads and contribute throughout the lifecycle—from product incubation and experimentation through production deployment, operation, and eventual transfer to business-aligned technology teams. What makes this opportunity particularly compelling is the combination of strong software engineering and applied AI. The team is building systems incorporating AI agents, agent orchestration, tool integration, retrieval-based systems, prompt engineering, evaluation frameworks, observability, and guardrails. The position is not focused on AI research or training foundation models. Instead, it focuses on practically applying modern AI technologies to build reliable, scalable, production-quality enterprise systems. The firm's AI Labs is focused on building the firm's next generation of data and AI capabilities and developing high-impact technology solutions that can ultimately be scaled across the organization. Responsibilities • Design, build, test, and deploy AI agents and intelligent systems for modern cloud-based, n-tier, cloud-native architectures., • Work closely with engineers, product owners, and business stakeholders to develop agent-driven workflows that automate complex processes and generate actionable insights., • Contribute to product incubation efforts by helping validate ideas, build robust implementations, and prepare solutions for production adoption., • Support the transition of proven capabilities through the Build-Operate-Transfer model, partnering with business-aligned technology teams for long-term ownership and scale., • Contribute to reusable AI capabilities across areas such as agent orchestration, prompt engineering, tool use, retrieval-based systems, evaluation frameworks, observability, and guardrails., • Champion engineering excellence by applying best practices in AI development, automated testing, code quality, continuous integration, and continuous delivery., • Manage technical debt and drive ongoing improvements in AI platforms and infrastructure., • Proactively seek opportunities to apply AI agents for increased business value and operational efficiency. Business & Collaboration Collaborate directly with business stakeholders and product owners to understand needs and priorities. Translate business requirements into effective and scalable technology solutions. Make technology decisions that support both current requirements and future business objectives while maintaining fiscal responsibility. Collaborate across engineering, data science, product, and business teams in a highly collaborative enterprise environment. The Ideal Candidate Would Have a Background: Required • BS or MS in Computer Science or a related technical field (or equivalent experience), with, • 2+ years of professional development experience in an object-oriented language (Java, Python, or JavaScript preferred)., • Hands-on experience with cloud-native architectures (AWS, Azure), containerized microservices, and agent frameworks., • Exposure to or strong interest in AI-enabled systems, intelligent workflows, or agentic applications., • Familiarity with modern AI engineering patterns such as agent orchestration, tool integration, retrieval-based systems, evaluation approaches, monitoring, or guardrails is a plus., • Strong analytical and problem-solving abilities., • Commitment to quality via automated testing, code reviews, and continuous delivery., • Results-driven with a passion for learning and staying current with emerging technologies., • A product mindset and comfort operating in a fast-evolving technology landscape. Preferred Experience contributing to reusable platform components or shared engineering capabilities. Solid understanding of financial markets and financial instruments. Experience working within asset management, financial services, or another complex enterprise technology environment is beneficial. An individual who has a passion for AI, loves solving deep and complex technical and business problems and wants to have an outsized impact through the systems and products they build. An individual with a passion for technology and engineering, a high level of intellectual curiosity, a commitment to excellence, and an unparalleled drive to deliver world-class solutions. Interested Candidates If you or anyone in your network would be interested in this opportunity, please send your resume to Jerry Goldberg at jgoldberg@jharlan.com or contact us directly at (212) 792-0099. About the Client The firm is a publicly owned global asset management firm with $1.8 trillion dollars of AUM. The firm offers funds, advisory services, account management, and retirement plans and services for individuals, institutions, and financial intermediaries. The talent and dedication of their people is critical to their success. They offer an opportunity for developing one's professional career while working with individuals trained in a variety of disciplines in a collegial and dynamic environment. They offer a broad range of competitive benefits on a global basis. They seek candidates who are high-energy self-starters who want to join an investment management firm on the leading edge of the global markets. The management team needs individuals of the highest professional caliber who are leaders, problem solvers, analytic, detail-oriented, and entrepreneurial. Everyone at the firm works side-by-side with the firm's senior management in a highly collaborative and charged environment. Successful candidates are: • Analytic and relentless in pursuit of the right answer, • Strong communicators who excel at rapid synthesis, • Able to demonstrate sound business judgment, • Able to digest complexity while maintaining an understanding of the big picture of business needs, • Team players who are energized by a collaborative enterprise The firm's employees maintain the highest professional and ethical standards. The firm has earned a reputation for honesty, fair dealing, and transparency in a competitive industry. They believe that these standards are the foundation for superior investment performance and are critical to delivering performance to clients Compensation SALARY RANGE: The salary range is $121,000 - $206,000 plus employees may also be eligible for annual discretionary incentive compensation. Actual compensation within that range will be dependent upon the individual's skills, experience, qualifications, location, and applicable laws. Work Flexibility: This role is eligible for hybrid work, with up to three days per week working from home. Benefits: The firm invests in its people through a broad range of programs and benefits, including: • Competitive pay and bonuses as well as a generous retirement plan and employee stock purchase plan with matching contributions, • Flexible and remote work opportunities, • Health care benefits (medical, dental, vision), • Tuition assistance, • Wellness programs (fitness reimbursement, Employee Assistance Program), • Paid time off for vacation, illness, medical appointments, and volunteering days, • Family care resources, including fertility and adoption benefit Work Authorization Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States (e.g., H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant work status). FINRA licenses are not required and will not be supported for this role. 'J Harlan Group, LLC' is an executive search and advisory firm specializing in recruiting for Financial Services, Management Consulting and Public Accounting companies. The organization is a global leader in professional staffing and consulting services working with major companies in the US and Global investment capitals around the world. Built by industry leaders to meet the talent demand needs for highly professional and specialized roles, J Harlan Group, LLC operates under the highest level of professional and quality standards providing a customized project approach for each client and search assignment.

Job DescriptionJob Title: IT Security Operations (6152-1) Duration: 12 months Location: New York Notes: This is an on-site role. Job Description • The Cybersecurity IAM Engineer / SailPoint IdentityIQ and Identity Security Cloud Developer & Architect is responsible for designing, engineering, and modernizing enterprise identity governance capabilities across hybrid cloud and on prem environments. This role blends deep SailPoint IdentityIQ and Identity Security Cloud development with IAM architecture leadership, including lifecycle automation, integration patterns, governance frameworks, and ServiceNow workflow orchestration., • The engineer will serve as a technical authority for identity lifecycle, access governance, directory integrations, and SailPoint platform architecture—ensuring secure, scalable, and compliant IAM operations aligned with Zero Trust principles., • SailPoint IIQ and ISC Developer/Administrator with Okta and Citizen IAM We're looking for a talented SailPoint IIQ and ISC Developer/Administrator to join our team. You'll play a key role in developing, administering, and maintaining our identity and access management (IAM) solutions, ensuring secure and efficient access across our organization. Expertise in Okta and Citizen IAM initiatives is a strong plus. • Design, implement, and maintain SailPoint IIQ and ISC solutions, • Develop and automate workflows, connectors, and application onboarding, • Administer and support Microsoft Entra ID (Azure AD), including Privileged Identity Management (PIM), • Integrate IAM systems with cloud platforms such as AWS, Azure, or GCP, • Implement and manage Okta solutions, with a focus on Citizen IAM and external user identity needs, • Conduct code reviews to eliminate redundancies and optimize system logic, • Identify and address IAM vulnerabilities early in the development process, • Collaborate with IT stakeholders and business owners to mature Role-Based Access Control (RBAC) andapplication onboarding programs, • Manage and integrate APIs, privilege access management (PAM) tools, SailPoint Access History, SailPoint Access Modeling and database platforms, • Test, deploy, and recommend patches and upgrades for IAM systems, • Migration from IIQ to ISC for the upcoming project 1. SailPoint IdentityIQ Engineering & Development • Develop and maintain BeanShell rules, custom workflows, lifecycle event logic, task definitions, and plugin modules., • Engineer custom connectors, aggregation jobs, reconciliation logic, and provisioning adapters., • Build scalable application onboarding frameworks, entitlement schemas, and role models., • Implement and optimize certification campaigns, policy enforcement, SoD controls, and governance reporting., • Extend IIQ using Java, REST APIs, SCIM, and custom UI components. 1. IAM Architecture & Solution Design • Define and maintain end to end IAM architecture, including identity sources, directories, governance layers, and provisioning flows., • Architect scalable identity lifecycle frameworks supporting joiner/mover/leaver automation, authoritative source alignment, and attribute driven access., • Design integration patterns between SailPoint IIQ and ServiceNow, including:, • Access request workflows, • Automated ticket creation and closure, • Provisioning orchestration, • Incident and change management alignment, • Catalog item governance and approval routing, • Establish RBAC/ABAC frameworks, role mining strategies, and access modeling standards., • Create architectural diagrams, data flow maps, and governance models for enterprise IAM programs., • Evaluate modernization opportunities (e.g., SailPoint SaaS, passwordless, adaptive risk, ServiceNow IAM modules)., • Lead design reviews, threat modeling sessions, and IAM roadmap planning with cybersecurity leadership. 1. Integration & Directory Services • Architect and implement integrations with Active Directory, LDAP, Azure AD/Entra ID, HR systems, cloud applications, and ServiceNow., • Develop REST/SOAP integrations, SCIM connectors, and custom provisioning logic., • Implement authentication and federation patterns using SAML, OAuth, OIDC, and MFA platforms., • Ensure directory hygiene, identity data quality, and lifecycle accuracy across systems. 1. ServiceNow Integration & Workflow Engineering • Design and maintain ServiceNow IAM workflows, including access request, approval routing, and fulfillment automation., • Integrate SailPoint IIQ with ServiceNow for:, • Ticket based provisioning and deprovisioning, • Automated incident creation for provisioning failures, • Change management workflows tied to IAM operations, • Catalog item governance and entitlement mapping, • Collaborate with ServiceNow platform owners to ensure alignment between IAM processes and enterprise workflow standards., • Optimize ServiceNow → SailPoint → downstream system orchestration for speed, accuracy, and auditability., • Support migration or redesign efforts when ServiceNow is used as a front end for IAM services. 1. Security Engineering & Governance • Apply Zero Trust, least privilege, RBAC/ABAC, and governance principles to all IAM designs., • Engineer automated controls supporting SOX, HIPAA, ISO 27001, and NIST compliance., • Conduct root cause analysis for provisioning failures, connector issues, workflow errors, and performance bottlenecks., • Partner with security architects to align IAM architecture with enterprise cybersecurity strategy. 1. Operational Support & Platform Stability • Support production IIQ environments, including break/fix, patching, upgrades, and performance tuning., • Maintain detailed technical documentation, architectural diagrams, and operational runbooks., • Collaborate with HRIS, infrastructure, ServiceNow, and application teams to resolve identity issues and improve lifecycle reliability. Skills/experience of the assigned staff: Required • 5–9 years in IAM engineering, with 5–10+ years of SailPoint IdentityIQ development., • Strong proficiency in Java, BeanShell, XML, JSON, SQL, and REST API development., • Deep understanding of IIQ object model, connector frameworks, workflow engine, and plugin architecture., • Hands on experience architecting integrations between SailPoint IIQ and ServiceNow., • Strong knowledge of directory services, identity stores, and authentication protocols. Security & Governance • Expertise in identity governance concepts, RBAC/ABAC, SoD, and policy enforcement., • Familiarity with compliance frameworks (NIST) About Us: Since 2000, Tri-Force Consulting Services (https://triforce-inc.com) has been an MBE/SDB certified IT Consulting firm in the Philadelphia region. Tri-Force specializes in IT staffing, software development (web and mobile apps), systems integration, data analytics, system automation, cybersecurity, and cloud technology solutions for government and commercial clients. Tri-Force works with clients to overcome obstacles such as increasing productivity, increasing efficiencies through automation, and lowering costs. Our clients benefit from our three distinguishing core values: integrity, diligence, and technological excellence. Tri-Force is a six-time winner among the fastest-growing companies in Philadelphia and a four-time winner on the Inc. 5000 list of the nation's fastest-growing companies.

Job Description CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. About the Role CoreWeave's MetalDev team is seeking an Operations Engineer to support the services and automation used during data center bring-ups and in production. Reporting to the Engineering Manager, this hands-on role is designed for an engineer who can handle routine production issues with growing independence while developing deeper expertise in service reliability, observability, and hardware lifecycle management. You will support the Redfish-based services and tools used to initialize, reboot, monitor, and recover infrastructure at scale. You will independently triage routine alerts and support requests, contribute to incident response and root-cause analysis, improve dashboards and runbooks, and deliver small automation or reliability changes with guidance on complex or high-risk work. You will work with NVIDIA GPU servers, BMCs, DPUs, Cooling Distribution Units, NVLink switches, power shelves, and custom hardware while collaborating with Fleet Operations, Hardware Engineering, Service Engineering, and hardware and firmware vendors. Approximately 80% of the role focuses on production operations, troubleshooting, and incident response. The remaining 20% focuses on improving monitoring, documentation, operational processes, remediation capabilities, and automation. Key Responsibilities Production Support and Troubleshooting • Monitor team-owned services and fleet health, identify unhealthy devices, and coordinate remediation using established tools and procedures., • Independently troubleshoot routine initialization, reboot, provisioning, and service-health issues, escalating complex or high-risk problems appropriately., • Investigate problems across applications, Linux systems, networks, BMCs, servers, DPUs, power equipment, and cooling infrastructure using logs, metrics, and diagnostic data., • Perform and validate approved remediation, ensuring services and devices return to a healthy state., • Participate in incident response, maintain clear operational communications, and contribute to root-cause analysis and follow-up actions., • Participate in the team's on-call rotation after completing onboarding and a readiness review. Observability and Reliability • Use Prometheus, Grafana, PromQL, logs, and service telemetry to investigate service and infrastructure problems., • Maintain and improve dashboards, alerts, and operational KPIs for team-owned services., • Identify noisy alerts, monitoring gaps, and recurring failure patterns, and recommend practical improvements., • Develop small scripts, tools, or automation that reduce manual effort and make remediation safer and more consistent., • Validate software, firmware, or process changes in test environments and support controlled production rollouts. Documentation and Collaboration • Create and maintain run-books, troubleshooting guides, escalation procedures, and service-support documentation., • Capture incident findings and operational knowledge so the team can respond consistently and prevent recurrence., • Partner with Fleet Operations and engineering teams to reproduce issues, determine ownership, and track problems to resolution., • Support hardware and firmware vendor cases by collecting diagnostic evidence, tracking status, and validating vendor-provided fixes., • Communicate clearly, seek feedback, share knowledge, and escalate early when impact or risk is uncertain. Minimum Qualifications • Two or more years of experience in technical support, systems administration, cloud operations, site reliability engineering, infrastructure operations, or a related technical field, or equivalent practical experience., • Working knowledge of Linux system administration, including logs, processes, services, filesystems, networking fundamentals, and command-line troubleshooting., • Working knowledge of Kubernetes, containers, and at least one public cloud platform or comparable distributed infrastructure environment., • Experience using monitoring and observability tools such as Prometheus and Grafana; familiarity with PromQL or a similar query language., • Scripting experience in Bash, or another shell scripting language., • Experience troubleshooting issues across software services, operating systems, networks, or physical infrastructure., • A methodical approach to problem solving, strong documentation skills, and clear written and verbal communication., • Experience participating in an on-call rotation or supporting time-sensitive production issues. Preferred Qualifications • Experience supporting Kubernetes applications or distributed production services., • Experience with incident response, escalation, root-cause analysis, or post-incident reviews., • Familiarity with servers, BMCs, Redfish, IPMI, server provisioning, or hardware lifecycle management., • Exposure to GPU infrastructure, DPUs, high-performance computing, power systems, cooling systems, or data center operations., • Experience improving dashboards, alerts, PromQL queries, run-books, or operational automation., • Experience collaborating with hardware or firmware vendors to investigate and validate fixes., • Bachelor's degree in computer science, engineering, information technology, or a related discipline, or equivalent practical experience.Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. • You enjoy working close to the hardware and are curious about how GPUs, servers, and data centers fit together., • You thrive in infrastructure environments where reliability, performance, and automation matter as much as features., • You like collaborating across hardware, platform, and product teams to solve complex, ambiguous problems.Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: • Be Curious at Your Core, • Act Like an Owner, • Empower Employees, • Deliver Best-in-Class Client Experiences, • Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $109,000 to $145,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment, • A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com. Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.