Trabajos vector control en Harrison, New JerseyCrear alertas

Job Description Company Overview With an annual budget of $2.3 billion and more than 7,000 employees throughout the five boroughs, the New York City Department of Health and Mental Hygiene (NYC Health Department) is one of the largest public health agencies in the world, serving 8 million New Yorkers from diverse ethnic and cultural backgrounds. We're tackling a broad range of public health issues with innovative policies and programs and getting exceptional results, but our work is never finished. The breadth of our innovative programs provides the widest range of choices for every member of our team. With grant funds from the Centers for Disease Control and Prevention (CDC), the NYC Health Department is undertaking an initiative to prevent, prepare for, and respond to the expanding multistate outbreak of Influenza A/H5N1 and strengthen readiness for any respiratory disease threat with the potential to result in large, disruptive outbreaks to communities. The selected candidate will be an employee of Public Health Solutions, a nonprofit organization which is the fiscal and administrative manager of the grant but will be supervised by the NYC Health Department. This is a grant-funded position ending in January 2027 The Division of Disease Control performs identification, surveillance, treatment, control, and prevention of 90+ infectious diseases. It is one of the largest Divisions within the Health Department with seven bureaus including the Bureau of Communicable Diseases. The Bureau of Communicable Diseases is responsible for the surveillance, prevention, and control of over 70 infectious diseases, including foodborne, waterborne, respiratory, zoonotic and vector-borne diseases. Within the Bureau of Communicable Diseases, the Community Outreach and Health Education Unit is a collaborative and cross-cutting team that is in development. The team works across diseases on planning outreach and engagement with communities impacted by infectious diseases and on developing health education materials for preventing and controlling infectious diseases. Job Description The NYC Health Department has an opening for an outreach coordinator and health educator. This position will help develop and foster relationships with members of the agricultural and animal health community in NYC and develop health education materials for various public and provider audiences. They will report to the Community Outreach and Health Education Unit lead. Duties • Coordinating health education initiatives related to avian influenza and respiratory diseases, in collaboration with the Respiratory Pathogens Unit, as well as assisting with initiatives on other diseases and conditions managed by the Bureau of Communicable Diseases (BCD) including foodborne, waterborne, zoonotic and vector-borne diseases., • Arrange and conduct in-person visits to poultry markets in NYC to develop and foster relationships in order to facilitate communication with owners and staff., • Establish and foster relationships with backyard flock groups in collaboration with partners at the NYS Department of Agriculture and NYC Parks Community Garden program,, • Explore ways to engage and share information with the public and people at high risk of exposure to infected birds or animals, and people at greater risk of severe disease., • Create materials for the provider community as needed to support rapid identification and appropriate testing of patients at risk of avian influenza testing,, • Working with disease subject matter experts to develop and implement theory- and evidence-based health education materials or initiatives with a focus on populations most at-risk for zoonotic and vectorborne diseases. Materials and initiatives may include instructional activities and other strategies to change individual health behavior, as well as contributing to bureau and agency driven organizational efforts, policy directives, mass media, and community-level programs., • Collaborating with subject matter experts in BCD to maintain disease specific webpages, fact sheets, and existing health education materials for both a public and provider audience., • Developing social media proposals that promote health using innovative, targeted, and timely posts. Evaluating metrics to inform future social media posts., • Understanding and addressing cultural differences, health inequities, and disabilities when creating content and materials. Qualifications: • Undergraduate or graduate degree in field related to health education., • Previous experience working in fields related to health education., • Capacity and willingness to travel within NYC and be in the field 50% of the time., • The ideal candidate for this position must be a pro-active and self-motivated individual with the ability to work in teams and in a highly dynamic environment with multiple stakeholders and timelines. Additional Desired Qualities • Experience developing health education material and performing outreach activities., • Experience with stakeholder engagement and project management., • Ability to effectively work independently as well as collaboratively and effectively on an interdisciplinary team., • Excellent communication (verbal & written) and interpersonal skills., • Desire to grow professionally, develop new skills, and willingness to explore novel approaches., • Experience working with the public health sector and coordinating projects involving multiple stakeholders., • Ability to prioritize and work in fast-paced environment with hard deadlines., • Proficiency in Microsoft Word, Excel, Outlook, and PowerPoint., • Fluency in Spanish, Mandarin, or Arabic. Benefits: • Hybrid Work Schedule., • Generous Paid Time Off and Holidays., • An attractive and comprehensive benefits package including Medical, Dental and Vision., • Flexible Spending Accounts and Commuter Benefits., • Company Paid Life Insurance and Disability Coverage., • 403 (b) + employer matching and discretionary company contributions., • College Savings Plan., • Ongoing training and continuous opportunities for professional growth and development. Additional Information: • This is a temporary grant-funded position ending January 2027., • This individual must reside in the tri-state area (NY, NJ, CT) by their confirmed start date., • Preference may be given to individuals residing in New York City (5 boroughs) or surrounding New York State counties., • This individual will be expected to work non-business hours during emergencies. At PHS, we place immense value on diversity within our teams, understanding that varied backgrounds and experiences significantly enhance our community and propel us toward our goals. If you find you don’t have experience in all the areas listed above, we still encourage you to apply and share your background and experiences in your application. We are eager to discover how your unique perspective can bring positive transformations to our team and help advance our mission of creating healthier, more equitable communities. We look forward to learning more about you! PHS is proud to be an equal opportunity employer and encourages applications from women, people of color, persons with disabilities, LGBTQIA+ individuals, and veterans. Monday-Friday 35 Hours Per Week

Job Description Position Summary: As an AI Developer, you will design, build, and optimize AI-powered tools, automations, and workflows that enhance creative production across Wellcom HOME. Working closely with production teams, engineers, creatives, and AI specialists, you'll transform business challenges into scalable AI solutions that improve efficiency, quality, and innovation. This role combines software development, AI integration, and workflow automation to create production-ready systems that support content creation, asset management, CGI, VFX, and marketing operations. Key Responsibilities: • Design and develop AI-powered applications, services, and internal tools., • Build scalable automation workflows that improve creative and production processes., • Integrate Large Language Models (LLMs), computer vision, generative AI, and machine learning technologies into existing production pipelines., • Develop APIs and backend services that connect AI solutions with internal systems., • Collaborate with creative, production, CGI, VFX, and technology teams to identify automation opportunities., • Optimize AI models for speed, accuracy, reliability, and cost efficiency., • Build reusable components and internal frameworks that accelerate AI development., • Troubleshoot production issues and continuously improve system performance., • Maintain documentation for AI tools, workflows, and technical implementations., • Stay current with emerging AI technologies and recommend innovative applications that enhance Wellcom HOME. Required Qualifications: • Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or equivalent experience., • Strong programming experience with Python., • Experience building applications using modern AI frameworks and APIs., • Experience working with REST APIs and cloud services., • Understanding of machine learning concepts and prompt engineering., • Experience with version control (Git)., • Strong problem-solving and analytical skills., • Excellent communication and collaboration abilities. Preferred Qualifications: • Experience with Generative AI platforms (OpenAI, Anthropic, Gemini, etc.)., • Experience using LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks., • Experience deploying AI applications to cloud platforms such as Azure, AWS, or Google Cloud., • Familiarity with Docker and containerized deployments., • Knowledge of vector databases and Retrieval-Augmented Generation (RAG)., • Experience integrating AI into production, marketing, media, or creative workflows., • Experience with image, video, or 3D AI technologies. Technical Skills: Programming • Python, • JavaScript / TypeScript, • SQL AI & Machine Learning • Large Language Models (LLMs), • Prompt Engineering, • Retrieval-Augmented Generation (RAG), • AI Agents, • Machine Learning fundamentals Cloud & Infrastructure • Azure, AWS, or Google Cloud, • Docker, • Git, • CI/CD Development • REST APIs, • Backend development, • Workflow automation, • Data integration Success in This Role: A successful AI Developer will: • Build AI solutions that streamline production workflows., • Improve operational efficiency through automation., • Deliver reliable, scalable AI applications for internal teams., • Collaborate effectively across creative, production, and engineering functions., • Drive continuous innovation while maintaining security, quality, and performance standards.

Job DescriptionGlobal Financial Firm located in Jersey City, NJ has an immediate contract opportunity for an experienced Java Developer. Pay Rate: $84.00 - $89.00 Negotiable based upon years of experienceSummary: • Work Mode: Hybrid, • Location: Jersey City, NJRequirements:, • Minimum 10 years of experience in the design and development of enterprise-grade Java-based systems., • Proficient in Java 17/21/25 LTS (Java 25 preferred), Core Java, Jakarta EE (J2EE), Spring Framework 7 / Spring Boot 4.x RESTful services., • Working knowledge of modern Java language features and JVM internals — GC tuning and performance profiling., • Expertise in databases such as Oracle or equivalent (PostgreSQL/MySQL) with strong SQL and PL/SQL programming skills; schema versioning via Flyway/Liquibase., • Proficient in using AI-assisted development tools such as Claude, GitHub Copilot, Devin, Cursor for code generation, review, and productivity., • Experience with multiple technologies and medium-to-complex distributed systems; well-versed with design standards, patterns, and enterprise frameworks., • Fast learner of new tools, frameworks, and technologies; comfortable working with distributed/cross-timezone teams., • Experience in event-driven architecture — Spring Boot components integrating with Apache Kafka and MQ (IBM MQ), including partitioning, consumer groups, idempotency, and transactional outbox patterns., • Excellent knowledge of Relational Databases, SQL, and ORM technologies (JPA 2/3, Hibernate 6) and connection pooling (HikariCP)., • Strong understanding of Spring Security 6 — OAuth2.0/OIDC, JWT-based stateless auth, RBAC/ABAC., • Familiarity with API design — REST with OpenAPI/Swagger, and exposure to high-performance service communication., • Resilience patterns using Resilience4j — circuit breaking, rate limiting, retries., • Caching and NoSQL exposure — Redis, MongoDB, Elasticsearch; awareness of vector databases (Pgvector) for AI/RAG-integrated services is a plus., • Exposure to Spring AI and LLM integration patterns (RAG workflows) is an added advantage., • Tools — Well versed with IntelliJ IDEA/Eclipse., • Test-Driven Development and automated testing: JUnit 5, Mockito, AssertJ, Cucumber/Gherkin, Testcontainers for integration testing, contract testing (WireMock/Spring Cloud Contract); JIRA, Maven/Gradle, SonarQube., • Experience with version control — GIT, Bitbucket, GitHub (including PR/branching workflows)., • Experience with Docker, multi-stage builds, Red Hat OpenShift, and Kubernetes (Deployments, ConfigMaps, Secrets, Ingress, HPA/KEDA autoscaling)., • Experience with CI/CD systems such as Jenkins, GitHub Actions, GitLab CI, or ArgoCD., • Observability exposure — Micrometer, Prometheus, Grafana, distributed tracing via OpenTelemetry/Zipkin/Jaeger., • Strong understanding of the full Software Development Life Cycle (SDLC)., • Experience in Agile methodologies — Scrum, sprint planning, and iterative delivery.

Job Description Experience : 10 years Key Responsibilities Traditional Cloud & Compute Optimization AWS Commitment Optimization: Container Cost Allocation: Architectural Efficiency: FinOps for AI & Tokenomics Governance Tokenomics Lifecycle Management:.GenAI Cost Control & us. Inference & AI for FinOps Operations Intelligent Automation: (VTags). Non-Deterministic Forecasting: Required Experience & Skills:3 years of direct experience in FinOps, Cloud Cost Management, and Cost Optimization, with a heavy emphasis on the AWS ecosystem.1 years of practical experience managing AI/ML infrastructure costs orgoverning LLM/GenAI token pipelines. 7 years of overall experience in cloud computing, infrastructure engineering, or IT financial management. Deep Technical Vocabulary: Clear understanding of AI infrastructure primitives, including GPU right-sizing, vector database scaling, context window economics, and prompt caching strategies. Financial Literacy: Ability to converse fluently with corporate CFOs regarding CapEx/OpEx shifts, TCO/ROI scenario analysis, and shifting metrics from "total token burn " to "value delivered per token. "Framework Mastery: Familiarity with the FinOps Framework (Inform, Optimize, Operate) and the newly emerging open standards from the Tokenomics Foundation and FOCUS (Framework for Open Cost Code). Certifications (Required): FinOps Certified Practitioner (FCP) or FinOps Certified Professional. AWS Certification (e.g., AWS Certified Solutions Architect Associate or SysOps Administrator).Desirables FinOps Foundation AI Value or Technology Value Certifications. Strong background in building data visualization pipelines. Academic background in Business, Finance, Data Science, or Computer Science.

Job Description Overview East West Bank is seeking an experienced Senior AI Engineering to design, build, and operationalize enterprise-grade AI and Generative AI solutions across the Bank. This senior technical leader will translate emerging AI capabilities into secure, scalable, production-ready banking applications that improve operational efficiency, risk management, customer experience, and employee productivity. The role is expected to be hands-on at the outset while helping establish foundational AI engineering capabilities, operating standards, and a small, high-performing AI engineering team. Responsibilities • Design, develop, and deploy enterprise AI and Generative AI applications for prioritized banking use cases (e.g., customer service, fraud detection, document processing, knowledge management, and operational efficiency), • Architect LLM-enabled solutions spanning retrieval-augmented generation, vector search, agentic workflows, MCP, model orchestration, tool/function calling, and human-in-the-loop controls., • Build production-grade services and APIs using Python, FastAPI or Flask, Azure OpenAI, Azure ML, Databricks, ADLS, and modern cloud-native patterns., • Integrate AI capabilities into enterprise applications, developer workflows, knowledge management platforms, automation, analytics, and decision-support processes., • Establish engineering practices for CI/CD, testing, model evaluation, observability, performance optimization, security, and responsible AI controls., • Establish reusable AI engineering frameworks, reference architectures, code standards, deployment patterns, and governance controls to accelerate enterprise adoption., • Partner with business, data, cybersecurity, risk, compliance, legal, and vendor teams to ensure solutions meet regulatory, privacy, auditability, and operational risk expectations., • Prototype rapidly with stakeholders, convert pilots into scalable implementations, and define measurable adoption and impact metrics., • Evaluate LLM platforms for accuracy, latency, cost, security, explainability, and fit for regulated enterprise use cases., • Support hiring, mentoring, and day-to-day technical leadership of AI engineers and cross-functional delivery teams., • Stay current with emerging AI technologies and advise leadership on practical opportunities, risks, and implementation tradeoffs., • Perform other duties as assigned. AI Fluency & Hands-On LLM Skills • Hands-on experience with major LLM platforms, including OpenAI ChatGPT/Codex, Anthropic Claude, Google Gemini, Microsoft Copilot/Azure OpenAI, AWS Bedrock, and open-source models such as Llama or Mistral., • Practical experience with prompt engineering, RAG, embeddings, vector databases, LLM orchestration frameworks, agentic workflows, evaluation frameworks, and hallucination mitigation., • Ability to design AI applications that include data protection, source validation, access control, logging, monitoring, traceability, and human review where appropriate., • Strong understanding of Responsible AI, model governance, prompt-injection risks, data privacy, and production controls for LLM-enabled solutions. Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience; advanced degree preferred., • 10+ years of progressive experience in software engineering, AI engineering, platform engineering or related technology leadership roles, including experience delivering production AI solutions, • Proven experience leading AI, data, automation, or emerging technology initiatives from strategy and experimentation through production delivery., • Strong hands-on engineering background in Python, API design, microservices, cloud architecture, distributed systems, data pipelines, CI/CD, testing, observability, and secure software delivery., • Deep experience with the Azure ecosystem, including Azure OpenAI, Azure ML, Databricks, ADLS, Azure AI Search, and related enterprise integration patterns., • Experience with LLM frameworks and tooling such as LangChain, LlamaIndex, Semantic Kernel, vector databases, model registries, evaluation frameworks, and monitoring/observability tools., • Strong process and data discipline, including data quality, lineage, metadata, workflow design, controls, operational risk, and measurable business outcomes., • Experience in financial services, banking, fintech, insurance, or another regulated industry with strong understanding of compliance, auditability, risk management, and governance., • Ability to lead cross-functional teams, influence senior stakeholders, mentor engineers, and translate complex AI capabilities into practical business solutions., • Strong executive communication skills, including the ability to define AI roadmaps, operating models, standards, adoption plans, and success metrics. Preferred Qualifications • Master's degree in AI, Computer Science, Data Science, Engineering, or a related field., • Experience establishing AI engineering teams, platforms, reusable delivery patterns, and enterprise AI standards., • Experience with copilots, enterprise search, intelligent document processing, workflow automation, and AI-enabled knowledge management., • Experience driving AI vendor evaluation and selection processes within regulated environments, • Familiarity with model risk management, third-party/vendor risk, privacy impact assessments, and regulated technology delivery., • Experience with MLOps/LLMOps, AI monitoring, evaluation pipelines, model/prompt registries, and production incident management., • Track record of mentoring senior engineers and building high-performing technical teams. Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.

Job DescriptionLead Applied Scientist New York, NY - hybrid 3 days onsite Full time - W-2 only In addition, you will be offered competitive target incentive compensation, with awards based on overall corporate and individual performance. On top of this, you will be eligible for a comprehensive and competitive benefits package which includes medical plans for you and your family, health and wellness programs, retirement plans, tuition reimbursement, paid vacation, and much more. Manager's call notes: • Doesn't need to come from insurance although it would be nice, • True technically brilliant person. They will have signoff authority on proposed changes and implementations, • Looking at code and making sure everything is good to go, • Doer and a thought leader, • PYTHON, panda, Azure, databricks, computer engineering background How does this role contribute to our collective success? Data and analytics are of critical importance for the company. Simply put, we want to turn data into information, that can be used to: • Enable decisions to be made with confidence, based on information not just intuition., • Be more proactive, using information to identify new opportunities, and getting to them before our competitors., • Realize cost savings, finding ways to make processes more efficient, enabling our people to focus on using their skills to further add business value.This team is working to transform the way in which we do business and to enable us to effectively leverage the latest AI advancements to our competitive advantage. The Data Science & AI Delivery Lead is a key leadership role within this team, acting as the deputy to the Head of Data Science & AI Delivery and ensuring the smooth day-to-day running of AI delivery operations. The Data Science & AI Delivery Lead is the technical delivery leader for AI, machine learning, and advanced analytics solutions. This role owns technical execution, engineering standards, solution architecture, deployment quality, and production delivery of AI capabilities. This role focuses on how solutions are designed, built, deployed, and scaled. What will you do in this role? The Data Science & AI Delivery Lead acts as the right hand to the Head of Data Science & AI Delivery, taking ownership of the day-to-day execution and coordination of data science and AI delivery across strategic projects and standalone use cases. You will play a hands-on leadership role — driving technical delivery, managing workstreams, and stepping in for the Head of when required. This is not a purely managerial role. You will be expected to work directly in the codebase, review and shape technical designs, and maintain deep fluency with the tools and techniques the team uses daily. Working closely with the Head of, you will ensure projects are delivered to a high standard, on time, and with strong stakeholder engagement. In this role you will be responsible for: Day-to-Day Delivery Leadership: • Own the operational running of AI delivery workstreams, ensuring the team is focused, unblocked, and delivering against priorities. Engineering standards, patterns, reusable frameworks, and delivery best practices., • Design reviews, implementation approaches, and production readiness reviews. Establish execution across all AI delivery workstreams. Lead architectural decisions, technical Act as the primary point of escalation when the Head of is unavailable. Own technical, • Project Management: Own technical delivery accountability from concept through production., • Ensure solutions meet security, governance, scalability, explainability, and operational support standards., • Technical Oversight & Contribution: Provide technical guidance on solution design, model selection, and architecture decisions, ensuring the team is taking the right approach for each use case., • Review code and technical outputs to maintain quality standards and contribute hands-on to Python-based development when needed, particularly during critical delivery phases or proof-of-concept work., • Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search)., • Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift., • Champion engineering best practices across the team, including code review standards, documentation, version control (Git), and a clear separation between experimentation and production-ready code., • Technical Strategy & Architecture: Own AI solution architecture and technical design standards., • Define engineering approaches for LLM applications, agentic systems, machine learning solutions, and AI platforms., • Lead evaluation of emerging AI technologies and determine appropriate adoption., • Establish standards for MLOps, AI observability, model lifecycle management, and responsible AI implementation., • Collaboration: Work closely with our Business Technology Solutions for solution architecture and delivery, and with the Program Office for planning deliveries, providing timelines, cost estimates, and status updates. Partner with Data Engineering to ensure data pipelines and Lakehouse structures support AI delivery needs., • Team Development: Support the Head of Data Science & AI Delivery in leading and developing a growing team of Data Scientists and AI Engineers, fostering a culture of excellence, collaboration, and continuous learning., • Mentor and coach team members through hands-on pairing, structured code reviews, and knowledge-sharing sessions on emerging techniques and tools., • Provide hands-on coaching through architecture reviews, code reviews, pair programming, model reviews, and technical mentoring., • Maintain technical credibility as a practitioner leader who remains actively involved in delivery., • Resource & Capacity Planning: Support the Head of in tracking the project pipeline, estimating costs (including cloud computing and API consumption), and managing resource allocation to ensure the team is effectively deployed against priorities., • Technology Vision: Stay current with the rapidly evolving AI landscape, including new foundation models, open-source frameworks, vector databases, orchestration tools (e.g., LangChain, Semantic Kernel), and evaluation methodologies. Bring new ideas to the team and lead proof-of-concept development to assess feasibility and value., • Deputising: Represent the Head of Data Science & AI Delivery in meetings, steering groups, and stakeholder forums as required, ensuring continuity of leadership and communication.You may also be required to take on additional duties, responsibilities, and activities appropriate to the nature of this role. This role reports to the Head of Data Science & AI Delivery. About You: We encourage you to bring your own experience and expertise to the table so, while there are some qualifications and experiences we need you to have, we are open to discussing how your individual knowledge might lend itself to fulfilling this role and help us achieve our goals. What you need to have: • Demonstrable experience delivering AI/ML solutions in a professional environment, with a track record of taking projects from concept through to production., • Strong technical knowledge, including expert-level Python proficiency and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow)., • Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing., • prompt engineering, RAG patterns, and vector search., • Familiarity with Generative AI concepts and tooling, including working with LLMs,, • A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions., • Cloud platform experience, preferably Azure, including services such as Azure OpenAI, Azure Machine Learning, or Azure AI Search., • Experience managing or leading technical delivery teams while remaining hands-on, with a track record of fostering a positive, high-performing team culture., • Excellent communication skills and the ability to translate complex technical concepts for business stakeholders., • Strong project management skills, including resource estimation, progress tracking, and meeting deadlines in a fast-paced, multi-priority environment., • A proactive, problem-solving mindset with the ability to operate independently and step up into a leadership vacuum when needed.What we prefer you have:, • Experience with advanced NLP techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models., • claims, or actuarial data., • Experience working in the (re)insurance industry, with an understanding of underwriting, fairness testing., • Knowledge of responsible AI practices, including bias detection, explainability, and Role Factors:In this role, you will typically be required to:, • Attend your local office at least three (3) days per week to meet and build relationships with colleagues and the wider business., • Engage in company activities to grow your network and build a strong team culture.

Job DescriptionSenior AI Engineer Remote Rate: $85/hour Client : confidential Mandatory Skill :Agentic AI; Generative AI; LLMs; LangChain We are seeking a Senior AI Engineer to design, build, deploy, and operate enterprise-grade Large Language Model (LLM) applications supporting business processes within a regulated financial services environment. The ideal candidate will have hands-on experience taking Generative AI solutions from design through production deployment and providing ongoing production support. This role requires deep expertise in LLM orchestration, RAG, AI evaluation, Python, cloud services, observability, and production-grade AI engineering. Key Responsibilities " Design and implement multi-step LLM pipelines, including: o LLM orchestration o Structured output generation o Tool/function calling o Error handling, retry, and fallback logic " Develop and maintain Retrieval-Augmented Generation (RAG) solutions, including: o Indexing strategies o Embedding model selection o Retrieval quality optimization " Build and maintain LLM evaluation frameworks and golden datasets to measure accuracy, consistency, and regression risk before production releases. " Establish and enforce quality gates for model, prompt, and configuration changes. " Implement observability for non-deterministic AI applications, including: o Tracing o Structured logging o Quality monitoring o Cost monitoring " Manage cost and latency performance of production AI workloads against defined budgets. " Partner with Product, Business, Risk, Compliance, and Security teams to translate business requirements into technical solutions and support review/approval processes. " Participate in code reviews, architectural decisions, and technical documentation. " Provide ongoing production support for deployed AI applications, including incident response, root-cause analysis, regression management, and remediation. " Mentor junior engineers and contribute to engineering standards and best practices. Required Qualifications " Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. " Minimum 5 years of professional software engineering experience. " Minimum 2 years of experience developing LLM/Generative AI applications. " Demonstrated experience deploying at least one enterprise-grade AI application into production and supporting it after launch. Enterprise Production AI Experience Must Include " AI solution serving real users or business processes, rather than only a proof of concept or internal pilot. " Accountability for non-functional requirements such as: o Availability o Latency o Cost management o Access control o Data handling o Auditability " Experience completing security and compliance reviews within a regulated or enterprise environment. " Post-production ownership involving: o Incident response o Regression management o Changes deployed against live traffic Technical Requirements " Hands-on experience with at least one LLM agent/orchestration framework, such as: o LangGraph o LangChain o LlamaIndex o Semantic Kernel o AutoGen o Amazon Bedrock Agents " Strong experience with LLM evaluation methodologies, including: o Dataset/golden dataset curation o Metric selection o Evaluation of non-deterministic outputs o Appropriate use of LLM-as-judge techniques o Established evaluation frameworks or custom evaluation harnesses " Strong proficiency in Python 3.11 , including: o Type annotations o Automated testing o Asynchronous programming " Experience building and operating cloud-based services such as: o REST APIs o Data pipelines o Event-driven workers " Experience working within codebases governed by automated quality gates and formal code reviews. Preferred Qualifications " Experience with Document AI / Intelligent Document Processing, including: o OCR o Structured field extraction o Scanned documents o Photographed documents o Handwritten source material " Experience designing human-in-the-loop workflows, including: o Confidence scoring o Selective automation o Escalation and review processes " Experience implementing business rules or policies as versioned and reviewable artifacts. " Experience with event-driven architecture, particularly Apache Kafka. " Experience with Kubernetes, Helm, and CI/CD pipeline ownership. " Experience with Infrastructure as Code, particularly Terraform. " Experience with: o Model selection o Model benchmarking o Fine-tuning o Distillation o Cost and quality optimization " Prior experience within financial services, insurance, healthcare, or another regulated industry. Technical Environment AI / GenAI " LLMs " LLM orchestration frameworks " RAG " Agentic AI " LLM evaluation and observability tooling Programming / Application Development " Python 3.11 " FastAPI " Pydantic Data / Database " PostgreSQL with vector extensions " Aurora PostgreSQL Cloud / AI Platform " AgentCore Infrastructure / DevOps " Kubernetes " Helm " Terraform " CI/CD Event-Driven Architecture " Apache Kafka Observability " Datadog " OpenTelemetry Key Must-Have Skills for Screening Python 3.11 | LLM/GenAI | RAG | LangGraph/LangChain/LlamaIndex/Semantic Kernel/AutoGen/Bedrock Agents | LLM Evaluation | Production AI Deployment & Support | Cloud Services/APIs | AI Observability | Enterprise Security/Compliance Most important screening point: The candidate should have actually deployed an enterprise-grade GenAI/LLM application to production and supported it post-launch. POC-only GenAI experience would not meet the stated requirement.

Job DescriptionThis is a highly embedded, client-facing engineering role. The individual will play a role of Forward Deployed Engineer and will work directly with Fixed Income business users, technology teams, quants, operations, and control functions to identify high-value AI use cases, translate business workflows into technical designs, and build production-grade AI solutions. This role is not advisory. The successful candidate will be expected to sit close to the business, understand front-office and operational workflows, write code, test solutions, debug issues, and help move AI use cases from concept to controlled production adoption. The ideal candidate combines strong software engineering skills, practical generative AI experience, and a consultative approach to working with senior business stakeholders in a regulated financial-services environment. Required qualifications • Bachelor’s degree in computer science, Engineering, Mathematics, Finance, or a related field, or equivalent practical experience., • Strong hands-on experience with Python and modern software engineering practices., • Practical experience building applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs)., • Strong understanding of prompt engineering, including prompt design, prompt testing, grounding, context management, and output validation., • Experience building AI or data-driven applications that use APIs, databases, cloud services, and enterprise data sources., • Ability to work directly with business stakeholders, lead discovery discussions, clarify ambiguous requirements, and convert business problems into technical solutions., • Strong communication skills and the ability to explain AI concepts, risks, and design choices in clear business language., • Experience working in agile, fast-moving environments where prototypes must quickly evolve into production-ready solutions. Preferred qualifications • Financial-services experience, ideally within capital markets, Fixed Income, trading, sales, risk, operations, or banking technology., • Familiarity with Fixed Income products such as rates, credit, securitised products, municipals, FX, or derivatives., • Experience with retrieval-augmented generation, vector databases, embeddings, semantic search, and document intelligence., • Experience designing AI evaluation frameworks, including test datasets, quality metrics, human review loops, and model performance monitoring., • Familiarity with enterprise AI governance, model risk management, compliance review, data privacy, and regulatory expectations in financial services., • Experience in a forward-deployed, consulting, client engineering, post-sales engineering, or technical delivery role., • Exposure to cloud platforms, secure APIs, authentication/authorisation, and enterprise integration patterns.

Job Description Job Title: Lead Full Stack Engineer, Enterprise AI Platform Location-Type: Hybrid NYC, NY Start Date Is: ASAP Duration: (contract, perm, etc) FTE Perm Compensation Range: $200-250k/yr bonus benefits Benefits: Eligible for Health, Dental, Vision, 401K, PTO Must be authorized to work in the U.S. This position is not eligible for sponsorship . DESCRIPTION & RESPONSIBILITIES Our client is seeking a Lead Full Stack Engineer to help build and scale an AI-first platform that amplifies the company's intelligence and enables smarter decisions, faster. This role is for a hands-on technical leader who operates across the full stack, shaping everything from the core services and data models that underpin our applications to the user-facing features that bring them to life. You will design and build backend services, canonical data models, and the frontend architecture, design system, and shared components used across our applications and you will use those same foundations to deliver end-to-end, AI-powered product experiences that translate complex data into intuitive, high-impact workflows. You will partner closely with Product, Design, and Data teams across the full arc of delivery, from foundational capabilities through the features built on top of them. The ideal candidate combines strong system design skills with a product mindset, and is equally comfortable defining durable abstractions and shipping polished, user-centric applications powered by modern APIs and AI capabilities. RESPONSIBILITIES: • Own the design and delivery of end-to-end experiences, from the backend services and data models that power them to the user-facing features built on top., • Collaborate with Product and Design to translate business requirements into intuitive, high-quality user experiences, and evolve the underlying services and interfaces to support them., • Define and evolve canonical data models, shared domain abstractions, and APIs (REST/GraphQL) that are scalable, intuitive, secure, and directly enable rich, data driven product experiences., • Model and manage complex entity relationships, including graph-like structures and hierarchical data, and surface them through interfaces users can reason about., • Build and maintain event-driven architectures (e.g., pub/sub, streaming) to support loosely coupled, extensible systems and responsive product behavior., • Implement fine-grained access control patterns (RBAC/ABAC), ensuring secure and auditable data access across services and features., • Design and integrate indexing and search capabilities (e.g., for retrieval, filtering, and AI use cases) and bring them into product experiences such as search, copilots, and recommendations., • Integrate AI/ML capabilities into product workflows in a user-centric way, shaping both the underlying services and the surfaces users interact with., • Shape the frontend architecture used across applications framework choices, structure, conventions, state management, data fetching, performance, and accessibility and apply it while building product features., • Partner with Design to evolve the design system, and build and maintain the shared UI component libraries and frontend core modules that product features are composed from., • Ensure reliability, scalability, and performance across services and user-facing features through observability, testing, and continuous iteration based on feedback and usage data., • Drive developer experience improvements that increase velocity and consistency across teams, supporting other engineers in adopting and extending shared capabilities., • Collaborate with DevOps and Security to implement secure and compliant patterns across the stack., • Mentor engineers through design reviews, code reviews, and technical guidance within the team. QUALIFICATIONS SERVICE / PERSONAL SKILLS: • Strong systems thinker with a product mindset able to design abstractions that scale across teams and use cases while staying grounded in user value and business impact., • Clear communicator who can explain complex data models, APIs, and tradeoffs to technical stakeholders, and collaborate effectively with Product, Design, and Engineering partners., • Highly collaborative, equally comfortable enabling other teams through well-designed shared capabilities and shipping end-to-end features cross-functionally., • Execution-focused and pragmatic, with a strong sense of ownership over quality, reliability, and outcomes across the full stack., • Curious and adaptable, especially in applying AI/LLM capabilities within structured data systems and real user workflows. REQUIRED QUALIFICATIONS: • 5 years of professional software engineering experience, with strong backend and full-stack capabilities., • Proficiency in Python & TypeScript, with hands-on production experience in frameworks such as FastAPI or Django on the backend; React, Vue, or Angular typically with a modern build tool such as Vite on the frontend., • Proven experience shipping user-facing products and features end-to-end, including the shared services, APIs, and data models that underpin them., • Strong expertise in data modeling, including relational and non-relational patterns, and experience with graph or relationship-heavy domains., • Deep experience designing, building, and consuming APIs (REST/GraphQL) and service-oriented architectures in product applications., • Solid understanding of frontend architecture, state management, and performance optimization, with experience building intuitive interfaces on top of complex, datarich domains., • Experience with event-driven systems (e.g., Kafka, Pub/Sub) and asynchronous processing patterns., • Strong understanding of access control systems (RBAC, ABAC, multi-tenant design)., • Experience designing or integrating search and indexing systems (e.g., Elasticsearch, vector search)., • Solid experience with cloud-native systems (in particular the AWS ecosystem), CI/CD, and observability practices., • Familiarity with AI/ML-enabled systems and integrating them into product experiences (e.g., RAG, entity resolution, semantic search, copilots, recommendations), including observability and evals for AI workflows, is a plus., • Experience in data-rich domains (e.g., real estate, finance, asset management) is a plus., • Embraces AI coding and actively leverages AI coding agents to augment day-to-day engineering work, treating fluency with these tools as a core part of the craft., • Exercises strong judgment about when to trust agent output and when to review closely or take the wheel, with a clear sense of the failure modes of current models., • Comfortable driving multiple agents in parallel on independent workstreams, orchestrating their work and integrating results efficiently., • Continuously thinks about agent harness improvements tooling, context, guardrails, feedback loops that expand the autonomy and reliability of AI coding agents over time. EDUCATION/DESIGNATIONS/LICENSES: • Bachelor's degree in Computer Science, Software Engineering, or related technical field required (or equivalent practical experience)., • Advanced degree is preferred., • Cloud certifications (e.g., AWS/Azure/GCP architecture or security certifications) are considered an asset.

Job Description Job Summary: We are seeking a highly experienced Senior Python Developer with 15 years of software development experience to design, develop, and deliver enterprise-grade applications and APIs supporting mission-critical banking and financial services platforms. The ideal candidate will possess deep expertise in Python development, API architecture, cloud-native technologies, and financial systems while working closely with architects, product owners, business analysts, and engineering teams to build secure, scalable, and high-performance solutions. Experience developing AI-powered applications, Generative AI solutions, or machine learning integrations is highly desirable. Key Responsibilities: • Design, develop, and maintain enterprise-scale Python applications supporting banking, payments, lending, wealth management, trading, or financial services platforms., • Architect and build secure, scalable RESTful APIs and microservices for internal and external financial applications., • Develop API integrations with third-party banking platforms, payment gateways, financial data providers, and cloud services., • Design highly available distributed systems capable of processing high transaction volumes with low latency., • Build reusable Python frameworks, libraries, and automation tools that improve development productivity and code quality., • Collaborate with solution architects, product managers, business stakeholders, QA teams, and DevOps engineers throughout the software development lifecycle., • Optimize application performance, scalability, security, and reliability across enterprise environments., • Develop and optimize SQL queries, stored procedures, and data processing pipelines supporting large financial datasets., • Participate in architectural reviews, code reviews, and technical design sessions while mentoring senior and junior developers., • Implement CI/CD pipelines and automated testing to improve deployment quality and software reliability., • Ensure applications comply with banking security standards, regulatory requirements, and enterprise governance policies., • Troubleshoot complex production issues and provide technical leadership for mission-critical applications. Required Qualifications:, • 15 years of professional software development experience., • 10 years of hands-on Python development experience building enterprise applications., • Extensive experience designing and developing RESTful APIs and microservices., • Strong knowledge of FastAPI, Flask, Django, or similar Python frameworks., • Experience building secure API authentication using OAuth2, JWT, OpenID Connect, or SAML., • Strong experience working within Banking, Capital Markets, Payments, Wealth Management, Investment Banking, or Financial Services organizations., • Deep understanding of object-oriented programming, software architecture, and design patterns., • Experience integrating enterprise applications through REST APIs, SOAP services, message queues, and event-driven architectures., • Strong SQL skills with experience using PostgreSQL, Oracle, SQL Server, MySQL, or Snowflake., • Experience with asynchronous programming, multithreading, and performance optimization., • Familiarity with Docker, Kubernetes, containerized deployments, and microservices architecture., • Experience using Git, GitHub, Bitbucket, or GitLab for version control., • Experience working within Agile/Scrum development teams., • Strong communication and stakeholder management skills. Preferred Qualifications:, • Experience developing AI-powered applications using OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, or other Large Language Models (LLMs)., • Experience integrating AI capabilities into enterprise applications using Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, semantic search, or vector databases., • Knowledge of machine learning frameworks such as TensorFlow, PyTorch, LangChain, LlamaIndex, Hugging Face, or Scikit-learn., • Experience with cloud platforms including AWS, Azure, or Google Cloud Platform., • Experience working with Apache Kafka, RabbitMQ, Redis, or other event-streaming technologies., • Experience building data pipelines using Pandas, NumPy, PySpark, or Apache Spark., • Familiarity with financial messaging standards including ISO 20022, FIX Protocol, or SWIFT., • Experience implementing observability using Prometheus, Grafana, ELK Stack, or Splunk., • Knowledge of cybersecurity best practices, encryption, identity management, and secure coding standards. Technical Skills:, • Programming: Python, SQL, Bash, JavaScript (preferred), • Frameworks: FastAPI, Flask, Django, • API Development: REST, GraphQL, OpenAPI, Swagger, gRPC, • Cloud: AWS, Microsoft Azure, Google Cloud Platform, • Containers: Docker, Kubernetes, • Databases: PostgreSQL, Oracle, SQL Server, MySQL, MongoDB, Redis, • Messaging: Kafka, RabbitMQ, • DevOps: Jenkins, GitHub Actions, Azure DevOps, Terraform, • Testing: PyTest, Unit Testing, Integration Testing, API Testing, • AI/ML: OpenAI, Azure OpenAI, Claude, LangChain, LlamaIndex, Hugging Face, Vector Databases, RAG, • Monitoring: Grafana, Prometheus, Splunk, ELK Stack Banking Domain Experience: Candidates should have experience supporting one or more of the following:, • Commercial Banking, • Retail Banking, • Investment Banking, • Capital Markets, • Payments, • Digital Banking, • Treasury Services, • Lending, • Credit Risk, • Wealth Management, • Trading Platforms, • Regulatory Reporting, • AML / KYC, • Fraud Detection, • Financial Data Platforms

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. What You'll Do: CoreWeave is constantly launching new services that change what customers can build on AI infrastructure, and the data layer is one of its most important new frontiers. As a Solution Specialist for Data Services, you are the person who opens that frontier. You identify new market opportunities where data architecture, mobility, and pipeline design unlock GPU adoption, and you drive the initial adoption of CoreWeave's newest data capabilities with the earliest customers across new industries. You turn what you learn in the field into direct input on the product roadmap, and you make the broader sales and solution architecture organization fluent in the value these new services create. About the role: As a Solution Specialist for Data Services, you operate at the leading edge of CoreWeave's go-to-market motion. Your job is not to run an established playbook; it is to create one. You take newly launched data services (high-throughput data movement, plus support for the databases, indexes, and data structures behind AI training, high-concurrency inference, and agentic workloads) into new accounts and new industries, prove their value with the first wave of customers, and establish the repeatable patterns that sales and solution architects use to scale adoption. Along the way you are the field's voice into engineering, translating what early customers need into the priorities that shape CoreWeave's data and storage roadmap. In this role, you will: • Own the commercial and technical strategy for net new customer wins in data infrastructure, where storage architecture, data mobility, and pipeline design are the primary buying triggers., • Drive new business opportunities where data migration complexity, egress costs, or multi-cloud sprawl are the barrier to GPU adoption at scale., • Translate customer requirements around data lakes, vector databases, and high-speed storage tiers into specific product feedback that shapes CoreWeave's storage roadmap., • Develop deal structures, technical playbooks, and benchmark narratives that help sales and SA teams accelerate storage-heavy opportunities., • Engage directly with enterprise buyers as the authoritative voice on data gravity, multi-cloud networking, and the total cost of moving workloads to CoreWeave., • Design the commercial framework for multi-petabyte data pipeline deals, including egress cost modeling and GPU utilization commitments, to support large enterprise closings., • Partner with capacity and infrastructure teams to maintain a competitive edge on storage efficiency, performance, and security across active and prospective customer deployments.Who You Are:, • 10+ years of experience in distributed systems, storage engineering, or data architecture, with a track record of applying that expertise to drive customer outcomes and revenue., • 5+ years working with multi-cloud networking and data transfer protocols (S3, rsync, WAN optimization) in a customer-facing or deal-shaping capacity., • Deep working knowledge of storage technologies including NVMe-over-Fabric, POSIX filesystems, and object storage, with the ability to translate that into commercial differentiation., • Experience deploying and tuning large-scale database clusters (SQL, NoSQL, or Vector) and positioning that capability against customer migration and modernization requirements., • Strong understanding of BGP, peering, and high-speed data interconnects as they relate to data gravity, egress cost modeling, and enterprise deal structure., • Familiarity with Kubernetes-native storage orchestration (CSI drivers, persistent volumes) and how it impacts workload portability and platform stickiness.Preferred:, • Experience driving new business or shaping product strategy in industries with high-density compute and data needs, such as Financial Services, Biotech and Life Sciences, or Media and Entertainment., • Prior background in technical sales, solution consulting, or product management supporting large-scale enterprise data infrastructure decisions., • Deep understanding of multi-cloud networking architecture and secure data egress and ingress strategies, particularly where compliance and data residency requirements are active deal variables., • Advanced degree in Computer Science or Engineering, or equivalent experience with a demonstrated ability to operate at the intersection of technical architecture and commercial strategy.Wondering if you're a good fit? 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 love translating boardroom goals into technical reality: you can explain high-level business strategy and low-level data architecture and storage tradeoffs in the same meeting., • You love acting as the bridge: between high-level sales strategy and deep storage and data-pipeline engineering., • You are an expert at navigating "The Room": you have a proven ability to manage complex, multi-stakeholder technical evaluations without losing momentum.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 organization's growth opportunities 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 $207,000 to $275,000. 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.

Job DescriptionAbout Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com. Role: Enterprise AI - Platform Engineer Location: New York City, Madison Square Park area Reports to: Head of Engineering Experience Level: 6+ years Work Model: Hybrid, with regular in-office presence Why Join Enterprise AI? Enterprise AI is building the platform that enables reliable deployment of AI systems across enterprise environments. As a Platform Engineer, you will build and operate the core of Turing's Enterprise AI platform, including platform services, the model gateway, multi-tenant infrastructure, CI/CD, infrastructure as code, and observability. The central challenge is creating repeatable deployments across environments Turing may not control, including client cloud accounts, dedicated instances, and sovereign installations. As a Platform Engineer, You WillBuild Core Platform Services Design, build, and operate the services that support the Enterprise AI platform, including platform infrastructure and the model gateway. Enable Enterprise Deployment Create reliable deployment systems for client cloud accounts, dedicated instances, and sovereign environments. Own Infrastructure and Delivery Systems Build and maintain CI/CD, infrastructure as code, and deployment tooling across environments using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices. Build for Reliability Design systems that support secure multi-tenant operation, reliable service ownership, and clear operational accountability. Establish Observability Build observability across the platform using service-level objectives, structured logging, metrics, tracing, and alerting. Build FinOps Visibility Develop telemetry that tracks model and compute costs by tenant. The Anti-Sell Hands-on software engineering: This is not a cloud-operations or ticket-queue DevOps role. You must be able to write production software and contribute deeply to platform services. Operational ownership: You will participate in on-call operations and incident response and help build the processes required to operate a production platform. Deployment complexity: The platform must operate across client cloud accounts, dedicated instances, and sovereign environments. Team accountability: The platform must be observable, operable, and maintainable by the team rather than dependent on one individual. Our Enterprise AI Platform Engineers Typically Have Production platform engineering experience: Six or more years of platform or infrastructure engineering experience supporting production SaaS. Customer-controlled deployment experience: Experience shipping a product that customers run in their own environment, including in a VPC, a self-hosted environment, or an air-gapped environment. Strong software engineering depth: Deep expertise in at least one backend language, such as Go, Ruby, Python, or TypeScript, with the ability to read and work across the others. Cloud and infrastructure expertise: Deep experience in at least one cloud and comfort working in a second, including private networking, KMS, IAM, Kubernetes, Helm, Terraform or Pulumi, and GitOps. Reliability and observability ownership: Experience carrying a pager, running incidents, and working with tools such as OpenTelemetry, Prometheus, or Datadog. Data and platform systems experience: Familiarity with Postgres, object storage, queues, and vector stores. Candidates whose experience is limited to cloud operations or ticket-queue DevOps without software engineering, or who have never operated multi-tenant systems, will not be a fit for this role. Top-Tier Candidates Will Have • Experience with model serving and model gateways, including vLLM, LiteLLM, or Triton., • Experience implementing SOC 2 controls in CI., • Experience deploying and operating AI systems in regulated or highly controlled environments.Values, • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value., • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection, • We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.Advantages of joining Turing, • Work at the frontier of AI, helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks., • Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS., • Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges., • Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies., • Move at the pace of AI innovation, with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.

Job Description Software Engineer - Fixed Income New York, NY - hybrid 3 days onsite 12 months This is a highly embedded, client-facing engineering role. The individual will play a role of Forward Deployed Engineer and will work directly with Fixed Income business users, technology teams, quants, operations, and control functions to identify high-value AI use cases, translate business workflows into technical designs, and build production-grade AI solutions. This role is not advisory. The successful candidate will be expected to sit close to the business, understand front-office and operational workflows, write code, test solutions, debug issues, and help move AI use cases from concept to controlled production adoption. The ideal candidate combines strong software engineering skills, practical generative AI experience, and a consultative approach to working with senior business stakeholders in a regulated financial-services environment. Roles and Responsibilities " Embed with banks Fixed Income teams in New York to understand business workflows, pain points, data availability, and AI opportunities. " Partner with traders, sales, research, operations, risk, compliance, and technology stakeholders to translate business requirements into AI-enabled solutions. " Design, prototype, and build generative AI applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs), prompt engineering, MCP integrations, orchestration, retrieval-augmented generation, and agentic workflows. " Develop AI solutions that support Fixed Income use cases such as knowledge retrieval, workflow automation, document analysis, trade support, client intelligence, operational exception handling, and management reporting. " Build retrieval pipelines across structured and unstructured data, including research, policies, procedures, trade-related data, market commentary, client documents, and internal knowledge repositories. " Apply prompt engineering techniques to improve model accuracy, consistency, explainability, and user trust. " Design evaluation frameworks to test AI outputs for accuracy, completeness, hallucination risk, relevance, and compliance alignment. " Work with technology and control teams to ensure solutions meet enterprise standards for security, data privacy, auditability, access control, and model governance. " Communicate technical trade-offs clearly to both engineering teams and business stakeholders. " Support user adoption by gathering feedback, refining workflows, and ensuring AI tools solve real business problems rather than becoming standalone experiments. " Identify reusable patterns, accelerators, and components that can be scaled across other financial services use cases. Required qualifications " Bachelor's degree in computer science, Engineering, Mathematics, Finance, or a related field, or equivalent practical experience. " Strong hands-on experience with Python and modern software engineering practices. " Practical experience building applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs). " Strong understanding of prompt engineering, including prompt design, prompt testing, grounding, context management, and output validation. " Experience building AI or data-driven applications that use APIs, databases, cloud services, and enterprise data sources. " Ability to work directly with business stakeholders, lead discovery discussions, clarify ambiguous requirements, and convert business problems into technical solutions. " Strong communication skills and the ability to explain AI concepts, risks, and design choices in clear business language. " Experience working in agile, fast-moving environments where prototypes must quickly evolve into production-ready solutions. Preferred qualifications " Financial-services experience, ideally within capital markets, Fixed Income, trading, sales, risk, operations, or banking technology. " Familiarity with Fixed Income products such as rates, credit, securitised products, municipals, FX, or derivatives. " Experience with retrieval-augmented generation, vector databases, embeddings, semantic search, and document intelligence. " Experience designing AI evaluation frameworks, including test datasets, quality metrics, human review loops, and model performance monitoring. " Familiarity with enterprise AI governance, model risk management, compliance review, data privacy, and regulatory expectations in financial services. " Experience in a forward-deployed, consulting, client engineering, post-sales engineering, or technical delivery role. " Exposure to cloud platforms, secure APIs, authentication/authorisation, and enterprise integration patterns.

Job Description As a Data & AI Engineer, you’ll build and deploy modern data pipelines and generative AI solutions on AWS — from scalable ETL/ELT workflows and cloud data platforms to production-grade RAG systems and AI agents. One engagement you may be designing and optimizing data pipelines using Glue, Lambda, and Redshift, the next you’re building GenAI applications powered by Bedrock, Claude, and vector databases to enable intelligent search and automation. You’ll work directly with clients to deliver end-to-end data and AI solutions that are secure, scalable, and production-ready. What You’ll Do: • Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR, • Creating and maintaining data extraction, transformation, and loading processes, • Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB, • Implementing data lakes using S3 and related AWS services, • Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude, • Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases, • Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex, • Writing and testing SQL queries and stored procedures, • Documenting technical solutions and providing knowledge transfer to customers, • Supporting the implementation of data governance and security controls, • Troubleshooting and resolving issues with data pipelines and AI services, • Participating in code reviews and implementing feedback, • Assisting with proof-of-concept implementations for customer engagements Required Skills: • 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development, • 2+ years of hands-on AWS experience with production deployments, • 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents), • Proven track record delivering production AI applications from concept to deployment, • Strong understanding of software engineering best practices (version control, testing, code review, documentation), • Experience working in agile/scrum environments with distributed teams, • Excellent problem-solving skills and ability to work independently with minimal supervision, • Strong written and verbal communication skills for client-facing interactions Preferred: • Technical familiarity with AWS data and AI/ML services and modern data engineering practices, • Hands-on experience with ETL/ELT processes and data transformation, • Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks, • Ability to write and optimize SQL queries across various database platforms, • Knowledge of data modeling concepts and best practices, • Strong analytical and problem-solving skills, • Eagerness to learn new technologies and keep up with cloud and AI innovations, • Excellent communication skills with the ability to explain technical concepts clearly, • Attention to detail and commitment to solution quality, • Collaborative mindset with strong teamwork capabilities, • Experience or interest in automation and infrastructure as code The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate’s professional experience, key skills, and education/training. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Title: Immersive Studio Developer/Operator FLSA Status: Non-Exempt / Full-Time - 1 year contract, with possibility of extension Location: Bronx, NY (On-site at La Central and/or Lehman College Studios) Compensation: $75,000-$85,000 About BronxNet: BronxNet is the public service multimedia network "of the people, by the people, and for the people of the Bronx." We broadcast local news, health awareness updates, cultural programs, and voter literacy initiatives across six cable and streaming channels globally. We have a mission to promote participatory media and civic awareness, while providing community access, workforce development, and experiential learning through leading-edge media resources including studios to independent media-makers, students, and community creators. Position Summary: The Immersive Studio Operator provides critical operational support for live & recorded studio and field productions. Additionally, the Studio Operator plays an integral role in BronxNet’s educational mission by assisting, guiding, and mentoring staff, community access producers, interns, and students in proper studio protocols and workflow execution. We are seeking a hands-on technical, creative, detail-oriented Immersive Media Studio Operator to drive our real-time virtual sets, augmented reality (AR), and extended reality (XR) workflows. In this role, you will work with Ross Video Voyager VR platform and Unreal Engine during live-to-tape and real-time broadcast productions. As well as other 3D software applications such as Blender, Cinema 4D, etc. Essential Functions & Responsibilities: Technical Operations: Operate a variety of studio and control room equipment, including multi-camera arrays, PTZ cameras, video switchers, teleprompters, digital audio boards, and LED lighting grids. Graphics & Playback: Manage and execute real-time on-air elements using systems such as Xpression Graphics, ensuring correct lower thirds, playback loops, and visual assets are deployed seamlessly. Control Room Support: Monitor signal integrity, waveform monitors, vector scopes, and audio/video levels to guarantee high-quality broadcast feeds Student & Intern Mentorship: Guide, instruct, and supervise production interns and students on proper studio workflows, equipment handling, and safety measures in alignment with BronxNet’s workforce training goals. Workplace Learning: Work cross-departmentally to contribute to internal training and knowledge-sharing sessions to advance staff proficiency in immersive media software and industry best practices for AR/XR/VR production. Asset Management: log, track, and report technical malfunctions or equipment failures to the engineering team. Other Duties: Perform other related duties as assigned to support organizational goals. Required Education & Experience: Education: Associate’s or Bachelor’s degree in Media Technology, Television/Broadcasting, Communications, or a related field (equivalent hands-on industry experience will be considered). Experience: 1–3 years of professional experience operating within a live television control room, multi-camera studio, or media production environment. Technical Skills: Proven proficiency in Ross Video Voyager graphics platform and Unreal Engine. As well as proficiency in 3D software applications such as Cinema 4D, Blender or similar programs. Knowledgeable in operating broadcast switchers, digital audio consoles, studio cameras, teleprompters, and media encoding/streaming software. High proficiency in Apple Final Cut Pro and Adobe Creative Cloud tools (especially After Effects, Premiere Pro, Media Encoder, and Frame.io) is strongly preferred. Communication: Excellent interpersonal skills with an ability to communicate technical workflows patiently and clearly to community members of diverse technical backgrounds. Grace Under Pressure: Ability to work well with tight timelines and deadlines, and thrive in pressure-driven production environments. Physical & Environmental Demands: Must be able to work on-site in studio control rooms and enclosed studio environments. Ability to stand or sit for prolonged periods during long production schedules. Must be able to safely lift, carry, and maneuver production equipment weighing up to 30 pounds. Willingness to work a flexible schedule, including occasional evenings and weekends based on studio production slates. Preferred Qualifications: Experience with cloud-centric media infrastructure and live-streaming workflows. Experience with IP-based broadcast workflows and network media systems Familiarity with CRM Databases a plus Windows & Mac Operating Systems Deep familiarity with or connection to the Bronx community. Bilingual language skills (English/Spanish) are a major asset.

Job DescriptionOur client, a 3rd-generation management consulting firm. They are now looking to add to their team and are hiring a AWS GenAI Consultant. New York or New Jersey office or work remotely Summary The client is looking for an AWS GenAI Consultant to join our team as a full-time employee in our New York or New Jersey office or work remotely. This person is responsible for the end-to-end discovery, architecture, development, deployment, and optimization of secure generative AI and agentic solutions on AWS. They will drive the delivery of well-constructed, testable code that produces measurable customer outcomes. As an AWS GenAI Consultant, you will implement technical solutions as part of a team for customer engagements. This role requires strong teamwork, communication, patience, and organization skills needed to drive customer success. Responsibilities • Help customers shape their journey to adopting generative AI and provide technical and strategic guidance from use-case discovery through production., • Consult, plan, design, and implement secure generative AI and agentic solutions with customers, • Architect and build production applications using Amazon Bedrock and Amazon Bedrock AgentCore, • Become a deep technical resource that earns our customer's trust, • Develop high-quality technical content such as reusable code, evaluation suites, reference architectures, and white papers to help our customers build on AWS, • Innovate on behalf of customers and translate your thoughts into action yielding measurable results., • Support solution development by conveying customer needs and feedback as input to technology roadmaps. Share real-world implementation challenges and recommend expansion of capabilities through enhanced and new offerings., • Assist with technical briefs and decision records that document use cases, model selection, architecture, controls, and operating models, • Assist with reference architecture implementations and reusable accelerators, • Support internal and external brand development through thought leadership:, • Work with Marketing/Alliances to write blog posts, • Work with Marketing/Alliances to develop internal case studies and demonstrations Qualifications • Professional experience architecting and operating production generative AI solutions on AWS, with hands-on expertise in Amazon Bedrock and Amazon Bedrock AgentCore, • Experience in customer-facing technology delivery involving agentic systems, retrieval- augmented generation, evaluation, guardrails, security, observability, and modern software engineering, • You must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. Sample Activities You'll Do Creating an Enterprise RAG Framework • Assist Customer with use-case prioritization, source-system analysis, data classification, and quality, latency, and cost requirements, • Assist Customer in the development of referenceable playbooks, supported by code examples for ingestion, parsing, chunking, embedding, and retrieval, • Assist Customer in the development of sample runbooks to implement Amazon Bedrock Knowledge Bases and managed or customer-managed data sources, • Retrieval Architecture - Designing semantic and hybrid search, metadata and access- control filtering, reranking, citations, and evaluation with fit-for-purpose vector stores., • Responsible AI Controls - Applying Amazon Bedrock Guardrails for prompt attacks, harmful content, denied topics, sensitive data, grounding, and Automated Reasoning checks.• Assist Customer with the development of a report and supporting sample code documenting the architecture, evaluation results, controls, and rollout plan Creating a Production Agent Framework • Assist in selecting an agent approach and framework based on business outcomes and constraints, • Assist Customer in the development of referenceable playbooks, supported by code examples for agent tools, memory, identity, policy, and observability, • Assist Customer in the development of sample runbooks to implement a secure, scalable agent platform:, • Agent Runtime - Building agents on AgentCore Runtime or with the AgentCore harness, including streaming, session handling, and failure recovery., • Tool Integration - Connecting APIs, AWS Lambda functions, and enterprise systems through AgentCore Gateway using MCP, OpenAPI, or Smithy., • Identity and Memory - Applying AgentCore Identity and Memory for authorization, session context, long-term preferences, and tenant isolation., • Action Governance - Using Policy in AgentCore and least-privilege permissions to enforce deterministic tool access and auditable actions., • Assist Customer with the development of a report and supporting sample code addressing agent security, operations, and governance as part of the playbook Creating a GenAI Evaluation and Delivery Framework • Assist Customers in defining GenAI capabilities, success metrics, and acceptance thresholds based on identified business outcomes, • Assist Customer with reviewing the GenAI architecture against identified business outcomes and the AWS Well-Architected Generative AI Lens, recommending actions to close observed gaps, • Provide Customer with AWS best practices for quality, security, privacy, resilience, cost, and operational excellence, • Assist Customer with defining the first iteration of a minimum viable product (MVP):, • Build a multi-turn assistant with Amazon Bedrock Converse APIs, streaming, and grounded citations, • Implement an enterprise knowledge assistant with Amazon Bedrock Knowledge Bases, • Deploy an agent to AgentCore Runtime and connect governed tools through AgentCore Gateway, • Enable AgentCore Browser or AgentCore Code Interpreter when isolated web interaction or sandboxed code execution is required, • Apply Amazon Bedrock Guardrails, IAM, AWS KMS, AWS Secrets Manager, and private connectivity controls, • Provision AgentCore Observability and Evaluations, Amazon CloudWatch dashboards, OpenTelemetry traces, alerts, and quality gates, • Assist Customer in developing and implementing the first MVP in a non-production environment, under Customer's direction and using AWS best practices, • Assist Customer with identifying next steps and proposing activities for a future follow-on engagement, • Provide knowledge transfer to Customer's stakeholders on the GenAI and agent frameworks Relevant Technical Tools • Primary Languages – Python, TypeScript/JavaScript, SQL, • Tooling, Services & Libraries – Boto3, AgentCore SDK, Strands Agents, LangGraph, LangChain, LlamaIndex, FastAPI, MCP, OpenTelemetry, Git, Docker, Terraform, pytest Core AWS Services • Generative AI – Amazon Bedrock, including Knowledge Bases, Guardrails, and evaluations, • Agentic AI – Amazon Bedrock AgentCore, • Data and Retrieval – Amazon S3, Amazon OpenSearch Serverless, Amazon Aurora PostgreSQL, • Application Operations and Security – AWS Lambda, Amazon API Gateway, AWS IAM, AWS KMS, AWS Secrets Manager, Amazon CloudWatch

Job Description Genesis10 is currently seeking a Senior Generative AI Engineer - Remote for a direct hire opportunity with a Global Law Firm located in New York, NY. You will join as a Senior Generative AI Engineer on the AI Acceleration Team, reporting to the Data Science Manager, and working with engineers, data scientists, and legal domain experts. This role is for an engineer who can own the full lifecycle of LLM-powered products, from rapid prototyping through production deployment. You will design, ship, and operate AI systems that extract intelligence from complex legal documents, orchestrate multi-step agent workflows, and deliver measurable accuracy improvements under real-world latency and cost constraints. Responsibilities: • Own production AI systems end-to-end: Design, build, deploy, and monitor LLM-powered document analysis pipelines (extraction, classification, risk flagging) that serve lawyers daily, meeting defined latency SLAs and accuracy benchmarks, • Transform legal data into structured, high-quality datasets that power our AI systems, • Design and ship agent workflows: Architect multi-step, multi-agent systems for complex legal tasks (e.g., due diligence, contract review, regulatory analysis) with robust state management, tool calling, and human-in-the-loop checkpoints, • Define evaluation and governance frameworks: Build golden test sets, automated eval pipelines, and regression suites. Implement guardrails (prompt firewalls, output filters, PII redaction) to ensure safety and regulatory readiness, • Optimise cost and performance: Manage token budgets across model providers, implement caching and batching strategies, and make data-driven build-vs-buy decisions on model selection (API-served, open-source vs. proprietary), • Collaborate with lawyers and product to translate ambiguous legal requirements Requirements: • At least 3 years of professional experience building and deploying AI systems, with at least 1-2 years focused on LLM/GenAI applications in production, • Deep experience with document-heavy NLP: extraction from complex layouts (PDFs, tables, scanned documents), entity recognition, and structured output generation, • Proven ability to design and optimise RAG pipelines and prompt architectures for accuracy, cost, and latency in production, • Strong Python engineering skills, with clean, tested, production-ready code, • Familiarity with at least one LLM orchestration framework (LangGraph, LlamaIndex, or equivalent) and at least one vector database (Pinecone, Weaviate, pgvector, or equivalent), • Experience with cloud platforms (AWS or Azure preferred) for deploying and monitoring LLM-backed services, including CI/CD, containerisation, and observability tooling, • Experience designing systematic evaluation methodologies for generative AI (automated evals, golden test sets, faithfulness/hallucination metrics), • Ability to own a workstream end-to-end: scope it, build it, evaluate it, ship it, and clearly communicate tradeoffs and results to non-technical stakeholders, • Comfortable with CI/CD pipelines, code review, version control, and shipping behind feature flags, • A genuine interest in legal work is essential Desired skills: • Experience in a startup or high-velocity AI team where you shipped frequently and wore multiple hats, • Master's or PhD in Computer Science, Computational Linguistics, Mathematics, or a related quantitative field, • Vector databases, retrieval systems, or knowledge graphs experience, • Familiarity with model-serving infrastructure (vLLM, TGI, Triton) and GPU-aware deployment, • Domain experience in legal tech, compliance tech, or other regulated industries where accuracy and auditability are non-negotiable, • Published research or significant open-source contributions in NLP, information retrieval, or generative AI, • Experience with knowledge graphs, ontologies, or semantic reasoning over structured legal data, • Experience with Spark or Databricks and related technologies Pay range: $200,000 - $240,000 annually Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! 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, and Illinois) 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.

Job Description Job Title: Senior Network Automation Engineer - AI/ML, AIOps & Network Operations Location: Jersey City, NJ / Charlotte, NC / Chandler, AZ Duration: Contract - 12 months Pay Range: NJ2-101-08-01,Jersey City- $104.62 (Pay Rate: $73.67) -Preferred location NC1-025-05-03, Charlotte -$99.73 (Pay Rate: $70.23)-preferred location AZ1-805-03-80, Chandler- $99.73 (Pay Rate: $70.23) Job ID: 411704 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Senior Network Automation Engineer - AI/ML, AIOps & Network Operations to join our dynamic team. The ideal candidate will have strong experience in Python-based backend development, network automation, telemetry integration, and applied AI/ML for operations and a proven ability to deliver safe, reliable automation and AI-assisted troubleshooting in production environments. Responsibilities: • Design and develop network automation services for event correlation, intelligent troubleshooting, and automated remediation., • Build automation that supports self-healing use cases with automated checks, safe remediation actions, and guided recovery steps., • Develop backend automation services using Python and Django with supporting data stores such as Redis for state and caching., • Integrate automation with monitoring, telemetry, and alerting systems to consume events and metrics in near real time., • Partner with Network Operations to identify repeatable operational patterns suitable for automation., • Collaborate with Monitoring and Telemetry engineers to ensure automation logic is driven by reliable data signals., • Implement guardrails, validation, and rollback logic to ensure safe production usage., • Contribute to testing, versioning, deployment, and operational support for automation services., • Provide production support and troubleshooting for automation services., • Document designs, runbooks, and usage guidelines for Operations teams., • Design and productionize ML solutions for anomaly detection, event correlation, incident classification, root-cause analysis, forecasting, and predictive maintenance., • Engineer and curate telemetry datasets, perform feature engineering, labeling, data quality validation, and model-ready transformations across metrics, logs, events, traces, and topology., • Develop AI-assisted troubleshooting using LLMs, RAG, embeddings, and enterprise knowledge sources with human oversight and deterministic controls., • Build and maintain MLOps pipelines for experiment tracking, validation, versioning, deployment, monitoring, retraining, and rollback., • Evaluate models using precision, recall, false-positive reduction, resolution accuracy, latency, reliability, and operational adoption., • Implement responsible AI controls including explainability, privacy, security, bias assessment, auditability, access control, drift monitoring, and safe fallback behavior., • Create APIs and reusable services that integrate AI/ML inference with event management, observability, orchestration, and ITSM platforms. Required Skills & Qualifications: • Strong software development experience in Python, including REST APIs, message queues, or workflow engines., • Experience building backend services using Django or similar frameworks., • Hands-on experience with Redis or equivalent in-memory data stores., • Solid understanding of enterprise networking including routing, switching, wireless, and SD-WAN concepts., • Experience integrating automation with monitoring, alerting, or telemetry systems., • Ability to design automation for reliability and safety in production environments., • Experience operating in high availability, failure-sensitive environments., • Strong communication and collaboration with engineering and operations teams., • Education: Bachelor's or Master's in Computer Science, Engineering, or related field., • Experience: 8-12 years in network engineering, operations, automation, telemetry, monitoring, data engineering, or applied analytics with production AI/ML delivery. Preferred Skills: • Experience with event correlation, rule-based automation, or decision workflows., • Familiarity with observability data, including metrics, logs, and events, as automation inputs., • Exposure to Infrastructure as Code and CI/CD practices., • Understanding of IT service management and incident workflows., • AIOps experience in network assurance, observability, incident reduction, or autonomous operations., • Experience with cloud AI/ML services, GPU workloads, or enterprise model platforms., • Familiarity with graph analytics or knowledge graphs for topology-aware correlation and root-cause analysis., • Experience designing evaluation datasets, offline and online tests, and operational acceptance criteria for AI-assisted automation., • Hands-on ML stack: pandas, NumPy, scikit-learn, and PyTorch or TensorFlow. Familiarity with Jupyter, MLflow or similar, containers, Kubernetes, and CI/CD. Experience with vector databases or enterprise search, and frameworks such as LangChain or Semantic Kernel. Role Logistics & Notes: • Approved sites and W2 rates: NJ2-101-08-01, Jersey City, NJ ($104.63/hr, preferred); NC1-025-05-03, Charlotte, NC ($99.74/hr, preferred); AZ1-805-03-80, Chandler, AZ ($99.74/hr)., • Hybrid schedule with a minimum of 3 days onsite per week., • Start month: As soon as a candidate is identified., • Interview process: 1-2 rounds. Video required. In-person required. Glider ID verification., • Contract-to-hire potential. Candidates must not require sponsorship now or in the future., • On resume: include current location, relocation plan, availability/start date, and cooling-off requirement if applicable. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: • Competitive compensation and benefits., • Opportunities for growth with global clients., • A supportive, inclusive culture that values innovation and people., • Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

Job DescriptionJob Title: AI Engineer Location: Newark, NJ (Hybrid – 3 days onsite) Duration: 6 months Salary Range: $56.00 - $58.00/Hour on W2 (Without Benefits). Applicants must be willing to work on W2 Job Description: Candidate Requirements: • Microsoft Certified: Azure AI Engineer Associate or Azure AI Apps and Agents Developer Associate will be given priority compared to other candidates., • If the candidate is certified, include the respective Microsoft Certification link in the resume. Without that certificate credential, the certification is not accepted.Role Overview:, • An Azure AI Foundry AI Engineer designs, builds, and deploys intelligent generative AI, agentic workflows, and RAG (Retrieval-Augmented Generation) applications., • This role requires coding with Python, orchestrating AI models, and adhering to responsible AI standards for enterprise scalability.Key Responsibilities: AI & Agent Development: • Design autonomous or semi-autonomous AI agents and RAG pipelines using Azure AI Foundry (formerly Azure AI Studio).Model Orchestration & Integration:, • Build and fine-tune large language models (LLMs) and integrate them with business applications, Copilot Studio, and data pipelines.Testing & Evaluation:, • Implement performance and evaluation tooling (such as RAGAS or TruLens) to assess grounding accuracy, reduce hallucinations, and ensure model explainability.Infrastructure Management:, • Develop scalable AI infrastructure and maintain reusable AI components in accordance with engineering best practices (version control, observability, CI/CD).Core Requirements & Skills: Technical Skills: • Proficiency in Python, prompt engineering, and utilizing frameworks like LangChain, Semantic Kernel, or crewAI.Cloud Experience:, • Deep understanding of the Microsoft Azure ecosystem, including Azure OpenAI Service, Azure Machine Learning, and Microsoft Fabric.AI Governance:, • Strong focus on Responsible AI and Model Context Protocol (MCP) to ensure security, privacy, and fairness in model outputs.Experience:, • Typically requires a bachelor’s degree in computer science or a related field, alongside 2–5+ years of software or AI/ML engineering experience., • 7+ years in Microsoft Azure.Programming & Machine Learning:, • Python (primary language)., • ML frameworks: TensorFlow, PyTorch, Scikit-learn., • Data pipelines and preprocessing., • Machine learning, deep learning, and statistics., • Data modeling and feature engineering.Model Deployment & MLOps:, • Model deployment and MLOps (e.g., MLflow, Docker, CI/CD).Development & Integration:, • APIs and microservices.Cloud Platforms:, • Azure ML, SageMaker, Vertex AI.Generative AI:, • LLMs (GPT, Llama, etc.)., • RAG (Retrieval-Augmented Generation)., • Prompt engineering and vector databases.

Job DescriptionWho we are The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it. Who you are Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. Operating as an internal forward-deployed engineer, you will partner closely across business units such as Go-To-Market, Finance, and Operations to translate operational challenges into AI-first engineering solutions. This is a highly autonomous and visible role requiring exceptional communication skills, a deep commercial mindset, and the technical ability to own systems end-to-end, from the LLM prompt layer through to production deployment to directly transform business outcomes. What you'll do • Partner directly with business leaders, operations teams, and Process Analysts to deeply understand their workflows, identify high-impact automation opportunities, and translate ambiguous business challenges into scalable engineering specifications, • Prototype, build, and deploy AI-powered applications and agentic workflows that transform manual business processes into seamless AI-first operations, • Serve as the technical translator and primary communicator between the Applied AI engineering team and non-technical business units, managing stakeholder expectations and iterating rapidly based on real user feedback, • Architect and maintain LLM-based systems in the field, including prompt pipelines, tool-calling integrations, and retrieval-augmented generation (RAG) setups tailored to specific business use cases, • Build and maintain robust data pipelines connecting source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability for your stakeholders, • Own the end-to-end production reliability and business impact of the systems you deploy, monitoring, alerting, and iterating on AI outputs to ensure continuous value delivery, • Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities to solve operational problemsWhat we're looking for, • 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production, • Exceptional communication and stakeholder management skills with the ability to explain complex technical concepts to non-technical business leaders and translate their needs into actionable architecture, • Strong commercial and product-driven mindset prioritizing business impact and user adoption over theoretical technical perfection, • Strong Python skills to write clean, maintainable code and build APIs, data pipelines, and backend services, • Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns including function calling, multi-step reasoning, and tool use, • Familiarity with data engineering fundamentals including SQL, data transformation, and cloud data warehouses such as Snowflake, • Experience with workflow orchestration tools (Airflow, Prefect, or similar) and cloud infrastructure (AWS), • Ability to work highly autonomously in a fast-moving, ambiguous environment, manage competing priorities, and ship iteratively alongside business counterpartsWhile not required, these are a plus:, • Previous experience in a Forward Deployed Engineering, Solutions Engineering, or highly client/business-facing technical role, • Experience with vector databases, embeddings, or semantic searchOur Stack, • Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited), • Datastores: MySQL, PostgreSQL, Snowflake, • Cloud: AWS, • Version control: Git & GitHub, • AI Tooling: Copilot on GitHub, • Observability: Datadog 4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate's application relative to the required job qualifications and responsibilities listed in the job posting. As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records. Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs — without regard to race, color, religion, sex (including gender identity, sexual orientation, and pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law. We are committed to providing a welcoming, accessible hiring experience. If you need a reasonable accommodation for any part of the application or interview process, please reach out to us at recruiting@metropolis.io.

Job Description Our client a leading asset management firm, located in New York City is looking to hire an AI Engineer to join their Business Technology and Data Team. This is a Full Time Position. Work will be conducted 3 days in office and 2 day from home. Citizens and those authorized to work in the U.S. are encouraged to apply. Qualified candidates should send their resumes (Word Format) along with salary expectations to Daniel@velocitysgi.com . SUMMARY The AI Engineer will work closely with the Investment Research team to design, build, and support AI-enabled tools that improve research productivity, insight generation, knowledge discovery, and investment decision support. This role will partner with research analysts, portfolio teams, business technology, data, compliance, and operations stakeholders to identify high-value AI use cases and deliver practical, secure, and scalable AI products. The ideal candidate has a strong AI/ML foundation and hands-on experience building AI products, including generative AI applications, retrieval-augmented generation, natural language processing, model evaluation, prompt engineering, data pipelines, and production-ready software engineering practices. The ideal candidate will support AI initiatives within the investment research area while helping establish reusable patterns, standards, and governance for responsible AI adoption. RESPONSIBILITIES • Partner with the Investment Research team to identify, prioritize, and deliver AI use cases that support research workflows, knowledge management, document analysis, data analysis, and decision support., • Design and build AI products and tools, including generative AI assistants, research copilots, summarization tools, semantic search, document intelligence, workflow automation, and analytics-enabled applications., • Develop retrieval-augmented generation solutions using structured and unstructured data sources, including research notes, filings, earnings transcripts, market data, internal documents, and approved external content., • Build and maintain data ingestion, preprocessing, embedding, vector search, model orchestration, and evaluation pipelines to support reliable AI applications., • Apply strong AI/ML, natural language processing, and software engineering practices to design scalable, secure, maintainable, and user-friendly solutions., • Evaluate models, prompts, data sources, outputs, and user feedback to improve accuracy, relevance, explainability, and adoption of AI tools., • Collaborate with data architects, data engineers, application developers, infrastructure, cybersecurity, and compliance teams to integrate AI solutions with enterprise platforms and controls., • Implement responsible AI practices, including access controls, human-in-the-loop review, auditability, data privacy, model risk awareness, content validation, and appropriate usage guidelines., • Prototype quickly with business users, translate research needs into technical requirements, and move successful prototypes into supported production solutions., • Create documentation for AI solution architecture, data flows, model behavior, prompt patterns, evaluation results, operating procedures, and support processes., • Monitor emerging AI technologies, tools, frameworks, and investment research use cases, and recommend practical opportunities for adoption., • Provide ongoing support, troubleshooting, enhancements, and user training for AI tools deployed within the investment research area. REQUIREMENTS • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field; Master's preferred., • 3 5 years of experience in AI/ML engineering, applied ML, or software engineering, with at least one AI application running in production., • Retrieval-augmented generation (RAG) end to end: document chunking strategy, embedding models, vector search, hybrid and metadata-filtered retrieval, and measuring retrieval quality (recall@k, relevance evaluation sets)., • Embeddings in practice: choosing and migrating between embedding models (e.g. OpenAI, Gemini, open-source), handling token and context limits, caching, and re-indexing large corpora without downtime., • Vector and relational databases: strong SQL and PostgreSQL, including pgvector or a comparable vector store (Qdrant, Weaviate, Milvus). Schema design for chunks, metadata, and multiple embedding versions., • LLM application engineering: prompt engineering, structured outputs, tool and function calling, agent workflows (including MCP or similar tool protocols), evaluation, and guardrails. Experience with Anthropic Claude and/or OpenAI APIs., • Production Python: batch pipelines that hold up at scale (memory-bounded processing, retries, API rate and token limits, idempotent re-runs), plus testing, version control (Git), logging, and clear documentation., • Unstructured financial documents: extracting and structuring SEC filings (10-K, 10-Q, 8-K, 20-F, 6-K), earnings-call transcripts, PDFs, and HTML, and cleaning messy enterprise data., • Data analysis: profiling, validating, and reconciling data from market-data providers (e.g. FactSet) and internal sources to support AI outputs., • Working with stakeholders works directly with portfolio managers and analysts to gather requirements, ships fast iterations, and explains AI trade-offs (accuracy, cost, latency) in plain language., • Governance: understands data privacy, security, and responsible AI in a regulated investment firm, including handling material non-public information (MNPI), access controls, auditability, and AI usage policy. PREFERRED QUALIFICATIONS • Experience in investment management, equity research, or financial services., • Scheduling and operations for data pipelines (Windows Task Scheduler, cron, Airflow or similar), and deploying to Azure and/or IIS., • Building lightweight internal tools and dashboards (HTML/JavaScript, charting libraries) on top of AI pipelines., • Experience setting up governed self-service AI for business users, such as shared prompt projects and review-and-deploy workflows., • Familiarity with LLM cost monitoring and model-selection trade-offs. KNOWLEDGE, SKILLS, AND ABILITIES • Product-oriented mindset with the ability to move from prototype to reliable enterprise solution., • Strong analytical, problem-solving, and critical-thinking skills with attention to accuracy, usability, and business value., • Ability to collaborate effectively with investment professionals, technology teams, data teams, and control functions., • Strong communication skills and the ability to explain AI capabilities, limitations, risks, and trade-offs to technical and non-technical audiences., • Curiosity and continuous learning orientation in a rapidly evolving AI technology landscape., • Strong documentation discipline, including solution design, testing results, support procedures, and user guidance. Salary 160k

Job Description Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. We are seeking an experienced Data Engineer to join our data team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data integration processes, and data infrastructure on AWS cloud. You will collaborate closely with data scientists, analysts, and AI teams to support analytics, machine learning, and Generative AI initiatives across the organization. Requirements Key Responsibilities • Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc., • Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics, reporting, and AI-driven use cases., • Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring., • Support data preparation and ingestion for AI/ML and Generative AI workloads, including handling structured and unstructured datasets., • Enable data pipelines that support LLM-based applications, vector embeddings, and knowledge retrieval systems., • Lead the migration of legacy data systems to modern cloud-based data architectures., • Develop and maintain CI/CD pipelines for data workflows and platform automation., • Collaborate with data scientists, ML engineers, and AI teams to ensure data availability for model training, inference, and GenAI applications., • Optimize data pipelines for performance, reliability, scalability, and cost-effectiveness using AWS best practices. Required Skills • 8+ years experience as a Data Engineer working with AWS cloud services., • Hands-on experience with AWS services such as S3, Glue, Lambda, Redshift, and related data platform tools., • Experience building data pipelines using Databricks, Apache Spark, and SQL., • Experience with Apache Airflow for workflow orchestration., • Strong understanding of data modeling, data lake/lakehouse architectures, and ETL/ELT frameworks., • Experience with CI/CD pipelines and version control systems (Git)., • Exposure to Generative AI or LLM-based applications., • Experience supporting data pipelines for AI/ML workloads., • Familiarity with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) architectures., • Experience working with LLM APIs or AI frameworks such as LangChain., • Understanding of MLOps workflows and model deployment pipelines. Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Job Description We are seeking a highly entrepreneurial Front Office Applied AI Engineer to sit directly with our Equities and Fixed Income Sales teams and transform how Sales operates through AI, automation, analytics, and workflow innovation. This is not a strategy role or a back-office technology role. We are looking for a builder who can work directly with salespeople, identify opportunities, rapidly prototype solutions, deploy them into production, and continuously improve them based on user feedback. The successful candidate will develop AI agents, copilots, CRM workflows, analytics applications, and productivity tools that improve client engagement, sales effectiveness, cross-sell opportunities, and management insight. Key Responsibilities: Build AI Solutions for Sales • Design and deploy AI agents, copilots, and workflow automations for Equities and Fixed Income Sales., • Build additional tools that help salespeople prepare for meetings, prioritize clients, identify opportunities, distribute research, and generate market commentary., • Create reusable prompt libraries, agent frameworks, and workflow templates., • Develop next-best-action, client prioritization, and cross-sell recommendation capabilities. Deliver Commercial Analytics • Build additional dashboards and analytics tools for Sales, Management, and COO teams., • Develop revenue, wallet share, market share, pipeline, client activity, and coverage analytics., • Integrate CRM, research, holdings, market activity, and sales data into actionable insights., • Automate recurring reporting and management information workflows. Engineer for Production • Design and build production-grade applications, APIs, workflows, and data products., • Apply modern software engineering practices including testing, source control, CI/CD, monitoring, documentation, and release management., • Partner with Technology, Data, Compliance, and Risk teams to deploy scalable and supportable solutions. Build Responsible AI • Implement evaluation and monitoring frameworks for AI applications., • Measure and improve quality, accuracy, hallucination risk, latency, cost, adoption, and user feedback., • Ensure solutions are controlled, auditable, permissioned, and compliant., • Build AI workflows that respect data entitlements, access controls, and governance requirements. Must Have Skills: Applied AI & Engineering • Expert Python and strong SQL skills., • Experience building production AI applications and agent-based workflows., • Experience with LLMs, prompt engineering, RAG, semantic search, vector databases, and agentic frameworks., • Familiarity with Azure OpenAI, Copilot Studio, Semantic Kernel, LangChain, CrewAI, AutoGen, or similar technologies., • Experience with APIs, workflow orchestration, data pipelines, and enterprise integrations., • Understanding of LLMOps, model evaluation, observability, monitoring, testing, and AI governance. Cloud & Platform Engineering • Experience deploying applications on enterprise cloud platforms., • Understanding of DevOps, CI/CD, containerization, identity management, monitoring, and access controls., • Ability to build solutions that scale beyond prototype environments. Data Governance • Experience working with sensitive business data in controlled environments., • Understanding of entitlements, information barriers, auditability, and permissioning., • Ability to build AI solutions grounded in approved and governed data sources. Commercial & Front Office Knowledge • Strong understanding of institutional sales workflows and client coverage models., • Familiarity with CRM workflows, client prioritization, research distribution, market commentary, and sales productivity tools., • Understanding of revenue attribution, wallet share, market share, pipeline management, and client analytics., • Working knowledge of Equities, Fixed Income, Credit, Rates, FX, Financing, or related capital markets businesses., • Ability to engage credibly with Sales, Trading, Research, COO, Technology, and Compliance stakeholders., • Sitting beside a salesperson discussing client coverage challenges., • Building AI agents and workflows in Python., • Writing complex SQL and data pipelines., • Designing dashboards and analytics., • Integrating enterprise systems and APIs., • Monitoring and improving AI performance in production., • Explaining technical concepts to senior business leaders., • Taking a solution from idea to production deployment. You thrive in ambiguity, move quickly, and care deeply about building products that people actually use. Success in the Role You will have: • Delivered multiple AI agents and workflow automations used daily by Sales., • Reduced manual administrative workload across coverage teams., • Improved CRM discipline, client prioritization, and sales productivity., • Enhanced cross-sell identification and meeting preparation., • Improved management reporting and commercial analytics., • Established scalable AI engineering, governance, and LLMOps practices across Global Markets Distribution. Helped build one of the industry's most technology-enabled institutional sales organizations.

Job Description Description: Job Description Data / AI Native Engineer Location: St. louis, MO/ Arlington, VA/ NYC, NY & NJ Remote is OK | Arlington & NY/NJ is hybrid Day-to-Day Job Duties: Design, build, optimize, and support enterprise-scale Databricks and AWS Lakehouse data pipelines using Spark and PySpark. Develop Databricks solutions leveraging Delta Lake, Medallion Architecture (Bronze/Silver/Gold), and Unity Catalog. Develop high-volume batch and streaming pipelines using PySpark, ensuring scalability, performance, reliability, data quality, and maintainability. Design and implement modern lakehouse engineering patterns including SCD Type 2, Change Data Capture (CDC), idempotent writes, schema evolution, and data contracts. Work across the AWS data ecosystem, including technologies such as S3, Glue, Lambda, EMR, Redshift, Kinesis, and related AWS services. Use GitHub Copilot and/or Claude Code CLI as part of the daily engineering workflow to accelerate application code, data-pipeline development, testing, debugging, optimization, and documentation. Rapidly develop proofs of concept and MVPs using AI-assisted development, while establishing clear paths to scalable production implementation. Apply AI capabilities directly within the data-engineering lifecycle, including use cases such as: AI-assisted schema inference Automated data-quality rule generation LLM-based anomaly detection AI-generated PySpark transformations Intelligent data validation and enrichment Build data foundations for AI-enabled products, including feature stores, vector stores, RAG data layers, embedding pipelines, and other AI-ready data architectures. Design and develop high-volume streaming pipelines using technologies such as Spark Structured Streaming, Kafka, Kinesis, and Databricks Auto Loader. Develop and orchestrate enterprise data pipelines using technologies such as Databricks Workflows, Delta Live Tables, Airflow, and dbt. Implement secure and governed data-engineering practices using Unity Catalog, including catalog/schema organization, access control, lineage, governance, and data discovery. Lead technically complex data-engineering initiatives, drive solution design, coordinate engineering activities, and help resolve complex platform and pipeline issues. Partner with architects, software engineers, product owners, source-system teams, governance teams, analytics teams, AI teams, and business stakeholders. Remain actively hands-on with PySpark, Databricks, AWS, and software-engineering activities, rather than operating solely as a people manager or high-level data architect. Basic Qualifications: Minimum 8 years of overall Data Engineering / Software Engineering experience delivering enterprise-scale data solutions. Minimum 5 years of strong hands-on Data Engineering experience, including design, development, optimization, and support of production data pipelines. Minimum 3 years of hands-on Databricks experience, including production experience with: Delta Lake Medallion Architecture Bronze / Silver / Gold Unity Catalog Minimum 5 years of hands-on Spark experience, with strong expertise in PySpark specifically, rather than Scala-only Spark development. Minimum 3 years of AWS data-platform experience, using services such as S3, Glue, Lambda, EMR, Redshift, Kinesis, or related AWS technologies. Minimum 2 years of experience leading complex data-engineering initiatives, technical workstreams, or engineering teams while remaining hands-on technically. Proven experience combining data engineering and software-engineering practices, including modular development, testing, source control, CI/CD, observability, and production support. Demonstrated daily hands-on use of GitHub Copilot and/or Claude Code CLI, with the ability to describe concrete examples of how these tools are used to accelerate engineering work. Demonstrated ability to build POCs and MVPs rapidly using AI-assisted development. Strong understanding of distributed data-processing principles, large-scale pipeline design, performance optimization, data quality, and production operations. Strong SQL skills and experience working with large enterprise datasets. Critical Screening Requirements: Candidates should be screened out if they do not demonstrate: Proven experience spanning Data Engineering and Software Engineering. Proven experience leading complex data-engineering initiatives or teams. Hands-on Databricks experience including Delta Lake, Bronze/Silver/Gold Medallion Architecture, and Unity Catalog. High-volume Spark and PySpark experience; Scala-only Spark experience is not sufficient. Strong experience with the AWS data ecosystem. Daily hands-on use of GitHub Copilot and/or Claude Code CLI with specific examples. Ability to use AI-assisted development to rapidly create POCs and MVPs. Travel Travel as required based on project and client needs. Degree Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related technical discipline, or equivalent professional work experience. Nice to Have (But Not a Must) 2 years of experience applying AI/Generative AI within data-engineering solutions, particularly: AI-assisted schema inference Automated data-quality rules LLM-based anomaly detection AI-generated PySpark transformations Experience building AI-enabled data products, including feature stores, vector stores, RAG data layers, and embedding pipelines. 2 years of high-volume streaming experience using Spark Structured Streaming, Kafka, Kinesis, Auto Loader, or equivalent technologies. Strong implementation experience with modern lakehouse patterns including: SCD Type 2 CDC Idempotent writes Schema evolution Data contracts Hands-on experience with dbt, Airflow, Databricks Workflows, and/or Delta Live Tables. Experience designing data platforms and pipelines supporting enterprise-scale GenAI, RAG, machine-learning, or agentic-AI solutions. Profiles That Typically Align Well Senior Data Engineer Lead Data Engineer Principal Data Engineer Data Platform Engineer Senior Analytics Engineer Data Engineering Manager with active individual-contributor responsibilities Profiles That Typically Do Not Align Traditional ETL Developer focused primarily on Informatica / Ab Initio / DataStage without cloud-native engineering BI / Report Developer Diagram-only Data Architect DBA Hadoop Administrator

Job Description About Lantern Lantern is the specialty care platform connecting people with the best care when they need it most. By curating a Network of Excellence comprised of the nation's top specialists for surgery, cancer care, infusions and more, Lantern delivers excellent care with significant cost savings to employers and their workforces. Lantern also pairs members with a dedicated care team, including Care Advocates and nurses, for the entirety of their care journey, helping them get back to good health, back to their families and back to work. With convenient access to specialists nationwide, Lantern means quality care is within driving distance for most. Lantern is trusted by the nation's largest employers to deliver care to more than 6 million members across the country. Learn more about us at lanterncare.com. Lantern is the specialty care platform, connecting people with high-quality, affordable specialty care close to home. We operate in a regulated healthcare environment (HIPAA, HITRUST, SOC 2), we handle protected health information at scale, and we are becoming an AI healthcare company, with AI adoption a top company priority. This Principal IAM Engineer is a senior level, individual-contributor role and the technical authority for identity at Lantern. In an organization where the security perimeter is effectively identity, you will own the identity control plane end to end, and you will determine who can reach PHI and under what conditions. You will set the identity standard, build the automation behind it, and hold the verification bar that other teams operate against. You will report to the CISO and partner closely with our IAM engineer and with the platform, cloud, and service delivery teams that execute alongside you. This is a hands-on principal seat, not a people-management role today, with a clear path to expand into a leadership role as the identity function grows. Our security philosophy is open by default, secure by design. Security exists to help the business move fast, safely, and the default answer is "yes, safely," because guardrails are built into the platform, pipelines, and tooling rather than enforced by someone saying no. Gates exist only where risk genuinely warrants them, and even then they are automated, fast, and transparent. Location: Hybrid - at least 3 days/wk in our NYC, NY offices Responsibilities: • Own the identity lifecycle: joiner, mover, and leaver provisioning and deprovisioning, automated from role- and attribute-based models (RBAC/ABAC), with deprovisioning verified against an entitlement inventory rather than assumed., • Own access management, including Conditional Access, phishing-resistant MFA, and privileged access on a Zero Trust model, with least-privilege by default, just-in-time (JIT) elevation, and enforcement confirmed on every access path rather than only saved., • Own directory and federation across Entra ID, single sign-on, SAML, OIDC, and OAuth2., • Own secrets and non-human identity, including API keys, service accounts, and workload identity, and maintain an owner registry for them., • Own key access governance and separation of duties in a model where another team operates the key management system., • Own identity automation and identity-as-code, building lifecycle and access controls as reviewable, version-controlled infrastructure (Terraform and policy-as-code) rather than manual configuration., • Own the identity-verification standard the service desk follows for password resets, MFA resets, and device enrollment. This is a hands-on control point, because helpdesk-initiated resets are a leading account-takeover vector. Key Deliverables in Your First Year: • Conditional Access enforced by default on PHI-facing applications, with enforcement verified., • Automated joiner, mover, and leaver provisioning and deprovisioning that meets its SLA every time., • A secrets golden path, with vaulted secrets, none in code, and a populated key-to-owner registry., • Strong, phishing-resistant MFA coverage on privileged accounts., • Documented runbooks and depth across the control plane, so no critical control depends on a single person. How You Will Work: You will set standards that partner teams execute. Service Delivery performs provisioning tasks and resets against the verification bar you own. Cloud Engineering carries cloud access, workload identity, and key-management operations, with key access governed by you. HR events are the sole trigger for lifecycle changes. The Governance, Risk & Compliance team independently attests to the entitlements you produce, and access certification deliberately sits outside this role so that the team reviewing access is not the team granting it. Holding those boundaries cleanly is central to the job. Requirements: • A minimum of 8 years in identity and access management, including principal- or staff-level ownership of an identity control plane., • Deep Microsoft Entra ID engineering, including Conditional Access policy design, phishing-resistant MFA, single sign-on, and federation across SAML, OIDC, and OAuth2, and verifying that enforcement takes effect across every access path, not only the expected one., • Identity lifecycle automation across cloud, SaaS, and privileged systems, with role- and attribute-based provisioning (RBAC/ABAC) and deprovisioning verified against an entitlement inventory., • Zero Trust identity design, including least-privilege, just-in-time (JIT) access, and risk-based or adaptive access controls., • Identity governance and administration (IGA) platform engineering, including privileged access management., • Automation and scripting (PowerShell, Python, or similar) to build lifecycle workflows and custom connectors., • Identity-as-code and policy-as-code practice, using Terraform with source-controlled change management (for example, GitHub)., • Secrets and non-human identity (API keys, service accounts, workload identity), and maintaining an owner registry for them., • Key access governance and separation of duties in a model where another team operates the key management system., • The ability to act as the technical authority for a function without formal people-management authority, working directly to a CISO., • Bachelor's degree in a relevant field, or equivalent professional experience. Strong Candidates Will: • Healthcare or another regulated environment where identity controls gate access to PHI., • Hands-on Saviynt with PAM, Azure PIM, and Keeper, or transferable depth in comparable platforms., • Experience remediating a Conditional Access enforcement gap or a deprovisioning failure, and making the structural change that prevented recurrence., • Passkeys and FIDO2, or phishing-resistant authenticator experience, aligned with NIST SP 800-63 Rev. 4., • Experience growing a technical scope into a broader leadership remit., • Microsoft Identity and Access Administrator certification, CIMP, or equivalent. Who Thrives in This Role: • Verified enforcement. You do not consider a control done until you have seen it working on every path., • Automation bias. You remove the manual step rather than documenting it more carefully., • Structural fixes. You solve the class of failure, not the instance., • Boundary clarity. You hold the standard with partner teams without taking over their execution., • Governance respect. You keep access certification independent rather than absorbing it. Benefits • Medical Insurance, • Dental Insurance, • Vision Insurance, • Short & Long Term Disability, • Life Insurance, • 401k with company match, • Flexible Time Off, • Paid Parental Leave The salary range for this position is $175,000 - $225,000 annually, based on experience, skills, and qualifications. This position is also eligible for an annual bonus, separate from and in addition to the base salary range listed above. Lantern provides this range in good faith in compliance with New York's pay transparency requirements. About You: • You use LOGIC in your decision making and understand that progress is critical to making change. You focus on the execution of your content while balancing a fast-paced environment and you take the time to celebrate both the small & big wins., • INCLUSION is a core tenant of your personal beliefs. A diverse and inclusive environment is incredibly important to you. You understand and desire to be a part of a diverse team with different experiences and perspectives & you cherish the differences in each individual that you interact with., • You have the GRIT, drive and ambition to tackle big problems. Big problems require big ideas and a team that supports new ideas., • You care deeply for your customers are driven to keep HUMANITY in all decisions. Your customers aren't just the individuals using your product. They are the driving factor in your motivation to make a change., • Integrity guides you in life. Focusing on the TRUTH vs. giving people the answers they want to hear., • You thrive in a Team Environment. Collaboration is key in innovation and creating change. These pillars of LIGHT are a reminder to our team that we are making a difference by providing guidance and support in navigating the often complex and confusing landscape of healthcare. We hope that through this LIGHT, individuals can find their way to the best care, resources, and support they need to get back to life. If this sounds like you, we would love to connect to speak further about career opportunities at Lantern. Please apply to our role & someone from our Talent Acquisition Team will reach out to help you navigate our interview process. Lantern does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

Job Description Junior AI Developer Job Title Junior AI Developer Job Summary We are looking for a motivated Junior AI Developer to join our AI and Machine Learning team. This role is ideal for recent graduates or early-career professionals who are passionate about artificial intelligence, machine learning, and software development. You will work with experienced engineers and researchers to develop, test, and deploy AI-powered applications, while gaining hands-on experience with modern AI technologies and best practices. Key Responsibilities Assist in designing, developing, and testing AI and machine learning models. Build and maintain AI-powered applications using Python and machine learning frameworks. Support data collection, preprocessing, feature engineering, and model evaluation. Implement and fine-tune machine learning and deep learning models under the guidance of senior team members. Develop applications using APIs for Large Language Models (LLMs) and Generative AI solutions. Assist in building Retrieval-Augmented Generation (RAG) applications and AI chatbots. Write clean, maintainable, and well-documented code following software engineering best practices. Debug, test, and optimize AI applications for performance and reliability. Collaborate with AI engineers, software developers, data scientists, and product teams. Stay updated on emerging AI, machine learning, and Generative AI technologies. Required Qualifications Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field. 0 2 years of experience in AI, machine learning, or software development (internships and academic projects are welcome). Good understanding of machine learning fundamentals and basic deep learning concepts. Proficiency in Python programming. Familiarity with machine learning libraries such as Scikit-learn, PyTorch, or TensorFlow. Basic knowledge of NLP, computer vision, or Generative AI concepts. Understanding of data structures, algorithms, and object-oriented programming. Familiarity with SQL and basic database concepts. Experience using Git for version control. Preferred Qualifications Hands-on experience with LLM APIs such as OpenAI, Anthropic, or Google Gemini. Exposure to frameworks such as LangChain or LlamaIndex. Basic understanding of prompt engineering and Retrieval-Augmented Generation (RAG). Familiarity with Hugging Face Transformers. Experience with REST APIs and JSON. Knowledge of Docker and Linux fundamentals. Personal, academic, or open-source AI projects showcased on GitHub. Technical Skills Python SQL Scikit-learn PyTorch or TensorFlow Pandas NumPy Hugging Face Transformers (preferred) LangChain (preferred) Git Docker (basic) Linux (basic) REST APIs Soft Skills Strong problem-solving and analytical skills. Willingness to learn new AI technologies. Good communication and teamwork skills. Attention to detail and commitment to writing quality code. Ability to adapt in a fast-paced, collaborative environment. Nice to Have Internship experience in AI or software development. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Exposure to vector databases and embeddings. Understanding of MLOps fundamentals and model deployment. Participation in hackathons, coding competitions, or AI research projects. Benefits Competitive salary and performance-based incentives. Mentorship from experienced AI engineers and researchers. Learning and certification opportunities. Flexible work arrangements. Collaborative and innovative work environment. Opportunity to work on real-world AI and Generative AI projects using modern technologies.

Job Description Overview East West Bank is seeking a highly experienced AI Governance to lead the design, implementation, and operationalization of the bank’s enterprise AI governance framework. This role is designed for a hands-on governance leader with deep expertise in AI governance, data governance, risk management, and regulatory compliance within highly regulated industries. The ideal candidate combines practical implementation experience with strong understanding of AI/ML technologies, enterprise controls, data risk, model risk, operational governance, and responsible AI practices. The role will partner across business, technology, data, legal, risk, compliance, audit, and operations teams to establish scalable governance processes supporting AI use cases from intake through production monitoring and enterprise adoption. This position is part of East West Bank’s Enterprise AI Strategy & Transformation organization, focused on scaling AI initiatives into governed, measurable, compliant, and enterprise-ready capabilities. Responsibilities • Lead the design and implementation of the enterprise AI governance framework, operating model, standards, controls, and governance processes., • Establish and operationalize governance processes for AI intake, inventory management, prioritization, risk assessment, technology gating, approval workflows, monitoring, issue remediation, and value realization tracking., • Drive governance activities across the full AI lifecycle including ideation, proof of concept, pilot, production deployment, monitoring, model review, and retirement., • Partner with business, technology, data, legal, risk, compliance, cybersecurity, and audit teams to ensure AI initiatives align with enterprise governance standards and regulatory expectations., • Define governance controls for AI-enabled solutions including data quality, lineage, privacy, explainability, human oversight, auditability, retention, access governance, and operational resiliency., • Establish AI governance reporting, dashboards, metrics, and executive-level transparency related to AI adoption, business value, risk exposure, control effectiveness, and remediation progress., • Lead governance processes related to LLM, Generative AI, RAG, intelligent automation, and advanced analytics solutions., • Evaluate AI technologies, platforms, and vendors to ensure alignment with enterprise architecture, security, compliance, operational, and risk standards., • Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments., • Translate governance policies into repeatable operational procedures, evidence requirements, controls, checklists, and implementation standards., • Promote enterprise AI governance awareness, adoption, and responsible AI practices across business and technology organizations., • Perform other duties as assigned. Qualifications • 8+ years of experience in AI governance, data governance, model risk, enterprise risk, compliance, data management, or related governance disciplines within financial services, fintech, insurance, or other highly regulated industries., • Strong hands-on experience designing and implementing enterprise AI governance frameworks and operational governance processes in production environments., • Demonstrated experience operationalizing AI governance across AI intake, inventory management, prioritization, technology assessment/gating, risk assessment, approvals, monitoring, remediation, and value/metrics reporting., • Deep understanding of AI risk, model risk, data risk, operational risk, privacy, explainability, bias, human oversight, and responsible AI principles., • Strong understanding of regulatory, compliance, audit, and governance expectations related to AI, model governance, data governance, and enterprise controls., • Hands-on experience governing AI/ML, LLM, Generative AI, RAG, and advanced analytics solutions within enterprise environments., • Strong familiarity with enterprise governance tooling including Microsoft Purview, Collibra, Alation, Informatica, MLflow, model registries, monitoring platforms, and AI observability solutions., • Practical understanding of cloud data and AI ecosystems including Azure, Databricks, Snowflake, AWS, GCP, and modern data platforms., • Strong understanding of metadata management, data lineage, access governance, data lifecycle management, retention, and enterprise data quality controls., • Experience partnering across business, technology, risk, compliance, legal, cybersecurity, audit, and operations teams to operationalize governance at scale., • Strong analytical, executive communication, and stakeholder management skills with the ability to translate complex AI and governance risks into actionable business decisions., • Bachelor’s degree in Information Systems, Computer Science, Data Management, Risk Management, Business Analytics, or related discipline. Highly Preferred • Direct experience governing enterprise AI/GenAI programs within banking or highly regulated industries., • Strong familiarity with banking regulatory frameworks and governance expectations including SR 11-7, BCBS 239, CCAR, CECL, AML/BSA, privacy, and enterprise risk management standards., • Experience governing LLM platforms including OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Bedrock, or open-source models., • Hands-on experience with AI governance related to RAG architectures, vector databases, AI monitoring, prompt governance, and model evaluation frameworks., • Experience implementing governance controls supporting AI explainability, fairness, auditability, monitoring, and evidence management., • Strong understanding of AI/ML lifecycle management, MLOps, model registries, and production monitoring frameworks., • Professional certifications such as CDMP, DAMA, Collibra, Microsoft Purview, risk management, or AI governance certifications., • Master’s degree or advanced degree in Data Management, AI, Risk Management, Computer Science, or related quantitative discipline. Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.

Job DescriptionApplied AI Researcher New Jersey, Jersey city GenAI / NLP / Agentic AI / Applied Machine Learning LevelResearch-focused Individual ContributorTarget / alternate titlesApplied Scientist; Research Scientist - NLP; AI Research Scientist; ML Researcher; NLP Scientist; GenAI Researcher; Applied ML ScientistCore keywordsapplied research, LLM, NLP, transformers, RAG, retrieval, model evaluation, experiments, robustness, embeddings, synthetic data, multimodal, PyTorch, Hugging Face, banking AI, AWS AI, AIRPRecruiter red flagsAcademic-only profile with no applied delivery; weak experimental design; cannot translate research into AIRP-ready business or engineering requirements; no awareness of regulated data constraints. Role purpose Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes that can become production-grade AIRP solutions. The role focuses on measurable business value, rigorous experimentation, model behavior, and safe translation of research into banking-relevant applications. Client-specific emphasis • Research must be grounded in enterprise business use cases, not generic AI experimentation., • Candidates should understand how model, retrieval, data, evaluation, latency, cost, and safety decisions affect production delivery on AIRP., • Cloud/AWS awareness is valuable because successful research outputs must be handed off to engineering teams building on AWS-hosted AIRP.Primary ownership, • Applied research agenda for LLMs, NLP, RAG, evaluation, multimodal AI, and agentic workflows relevant to enterprise use cases., • Prototypes, experiments, benchmark design, model-selection recommendations, and production-readiness evidence., • Research-to-production handoff with AI engineering, AIRP platform, product, risk, and governance teams.Key responsibilities, • Conduct applied research in LLMs, GenAI, NLP, information retrieval, multimodal AI, synthetic data, and agentic AI., • Design experiments to evaluate model performance, robustness, safety, scalability, interpretability, enterprise usefulness, and production feasibility., • Prototype AI solutions for KYC, credit underwriting, governance tracking, pitch book generation, Banker 360, Customer 360, deal library intelligence, financial crime quality, and sanctions screening., • Develop evaluation methodologies using golden datasets, adversarial testing, offline benchmarks, human review, business outcome metrics, and risk-specific acceptance criteria., • Assess prompt optimization, RAG, fine-tuning, instruction tuning, synthetic data generation, distillation, and model adaptation techniques., • Document model limitations, data assumptions, hallucination patterns, bias risks, performance boundaries, and control recommendations for regulated deployment., • Collaborate with engineers to convert prototypes into production-ready AIRP requirements, including latency, cost, observability, security, and AWS/cloud deployment considerations., • Track emerging AI research and translate relevant advances into practical recommendations for the enterprise.Must-have candidate profile, • Advanced degree preferred, usually MS or PhD in AI, ML, computer science, statistics, computational linguistics, mathematics, or related field., • Strong foundation in machine learning, deep learning, NLP, transformers, information retrieval, and generative AI., • Hands-on experience with LLMs, embeddings, RAG, model evaluation, and applied GenAI experimentation., • Python skills with PyTorch, TensorFlow, Hugging Face, scikit-learn, or equivalent research frameworks., • Ability to design rigorous experiments and communicate findings to technical, product, business, risk, and governance stakeholders., • Ability to translate research results into production requirements suitable for an AWS-hosted enterprise platform.Preferred experience, • Research or applied science experience in banking, finance, compliance, risk, legal, operations, financial crime, sanctions, or enterprise knowledge systems., • Experience with AWS Bedrock, SageMaker, vector search, MLflow, Databricks, model evaluation tooling, or cloud-based experimentation environments., • Publications, patents, internal research contributions, open-source AI contributions, or prior research-to-production handoffs., • Familiarity with Responsible AI, model validation, privacy constraints, audit documentation, and regulated deployment environments. Regards, Sr. Technical Recruiter Shubham Chandra Shubham.c@echoitsol.com

Job Description We build AI agents that actually work in enterprise environments — not prototypes, not demos. We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that are model-agnostic and built to last. You'll be deployed on client engagements as the lead technical architect and builder of agentic systems running in AWS, OCI, and Azure. You'll work directly with client stakeholders, translate complex requirements into working systems, and leave behind infrastructure clients can operate and extend. You'll also help Trilagen productize our delivery approach as we scale the practice. If you've only ever built agents that run on your laptop, this isn't the role. If you've shipped agentic systems into production cloud environments and know exactly what breaks and why — we want to talk. What you'll own Full-stack agent development You design and build the entire application — not just the AI layer. This means a React or Next.js frontend with streaming, real-time agent UX; a Python or Node.js backend that orchestrates agent logic, manages state, and exposes clean APIs; and containerized, cloud-deployed services that operations teams can actually run. You own the repo, the CI/CD pipeline, the deployment, and the runbook. Multi-cloud deployment Production agent systems on all three major clouds: AWS (Lambda, ECS/Fargate, Bedrock, API Gateway), Oracle OCI (OKE, Functions, AI Services), and Azure (AKS, Azure OpenAI Service, Azure Functions). You understand the tradeoffs between platforms and can advise clients on where to run what and why. LLM integration and model strategy You have deep, hands-on experience with the leading LLM providers and their APIs — Anthropic Claude (Messages API, tool use, streaming, context management), OpenAI (GPT-4o, Assistants API, function calling), and Google Gemini (Gemini Pro/Flash, Vertex AI). You architect model-agnostic integration layers so clients aren't locked in, and you know how to select, swap, and benchmark models for specific agent tasks. Agentic architecture You understand how to design systems that do real multi-step work: tool use and function calling patterns, ReAct and plan-and-execute loops, agent-to-agent orchestration and handoffs, human-in-the-loop checkpoints, retry and failure recovery strategies, and cost/latency optimization across long-running agent workflows. Frameworks like LangGraph, CrewAI, AutoGen, and the Model Context Protocol (MCP) are tools in your toolbox, not the ceiling of your knowledge. Memory and context layer You've designed and implemented memory architectures for production agents: short-term conversational context, long-term persistent memory, RAG pipelines with vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and identity layer This is non-negotiable for our client base. You build the security envelope around every agent system you ship: OAuth 2.0 / OIDC authentication flows, API key lifecycle management, role-based access control enforced within agent workflows, secrets management (AWS Secrets Manager, Azure Key Vault, OCI Vault), audit logging for agent actions, prompt injection defense, and data residency controls. Familiarity with Okta or SailPoint ISC is a direct advantage on our engagements. Requirements • 4+ years of software engineering experience with at least 2 years building and shipping LLM-powered or agentic applications in production cloud environments, • Hands-on depth with at least two of the three major LLM providers: Anthropic Claude, OpenAI, and Google Gemini — at the API level, not just via wrappers, • Full-stack proficiency: Python (FastAPI, Flask, or similar) backend, React or Next.js frontend, REST and WebSocket API design, • Production experience on at least two of: AWS, Azure, OCI — with real deployments, not sandbox accounts, • Demonstrated ability to design and implement agent memory and retrieval systems using vector databases and RAG, • Strong command of AI security practices: auth, RBAC, secrets management, audit logging, and prompt-level safeguards, • Consulting DNA — you can run a discovery session, write a technical design doc, manage client expectations, and own delivery end to end Nice to have • Experience with all three LLM providers (Anthropic, OpenAI, Gemini) and model-agnostic orchestration patterns, • Okta and/or SailPoint ISC integration experience, • Cloud certifications: AWS Solutions Architect, Azure Solutions Architect, OCI Architect Benefits Benefits: • 401K, • Health Insurance, • Dental Insurance, • Paid Time Off, • Paid Sick Leave

Job DescriptionCompany Description EBG powers a proprietary suite of e-commerce platforms and technology solutions to deliver exclusive deals and special offers from the world's top brands and experiences. Specializing in live entertainment, travel, retail products and services, EBG operates a network of employee and membership-based marketplaces with a reach exceeding 100 million users. EBG owns the nation’s most comprehensive employee savings program, serving over 40,000 corporate clients through its B2B2C platforms TicketsatWork, Plum Benefits, Working Advantage, and Beneplace and offers additional value through its loyalty program, FunLife Rewards. Undercover Tourist®, a prominent online travel site, is owned by EBG. Visit www.ebgsolutions.com to learn more about EBG and its commitment to connecting people to exceptional experiences. EBG’s people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. We believe in the value of working near our colleagues, and we foster and prioritize meaningful in-person connection whenever possible. EBG primarily hires within our core cities—Orlando, New York, Austin, Las Vegas, and Aventura (Miami) with a focus on candidates located within a commutable distance to collaboration offices within these markets. Job Description This role is Work from Home (WFH). All candidates must be within commutable distance to a local office in NYC or Miami for Quarterly Company Events in a hirable state. We do not provide sponsorship and we do not hire from outside the USA. The Email Developer will be responsible for the coding, creation, execution, scheduling, and analysis of all email programs across multiple platforms and brands. In this role, they will collaborate with internal business partners to execute and scale email campaigns that are critical to driving growth. They will maintain an ongoing awareness of trends and best practices of email design and coding principles. In addition, the email developer will work closely with all members of the Marketing and Product teams in multiple offices to ensure seamless execution. Responsibilities • Develop complex and customized HTML/CSS code, including the following:, • Ability to code complex email templates from scratch, modify/update existing templates, and troubleshoot existing email code as needed., • Provide technical guidance and expertise on how to make our emails more automated and personalized, through knowledge of advanced coding and scripting techniques., • Create custom email templates using HTML, CSS, and liquid scripting to create clean, responsive, modular code that can connect and utilize data sources, logic, and segmentation to populate dynamic offers within email campaigns, be it stand-alone campaigns or automated experiences/journeys., • Develop customer experiences/journey flows utilizing logic, rules, and segmentation criteria., • Code with “mobile-first” mindset and adheres industry best practices for email coding and development., • Use AI-assisted development tools and agents to accelerate email coding, testing, troubleshooting, and architectural enhancements, and integrate AI agents into email and CRM workflows., • Manage end-to-end email production that supports our eCommerce business – including: coding, development, deployment, and analysis of email campaigns, utilizing a major ESP (i.e., Zeta, Salesforce Marketing Cloud, etc.). This also includes, but is not limited to:, • Participating in the QA/QC process for all email campaigns, working with account managers, marketing leads, and developers to ensure all details, links, spelling, products, and content are correct., • Coordinating with cross-functional account managers on campaign assets, reviews and approvals., • Collaborating with merchandising and marketing teams on campaign calendars., • Leverage existing segments and create new custom segments for email deployment utilizing data within the email service provider/platforms. Partner with marketing & data analytics for additional custom segment creation that falls outside the scope of the ESP., • Use problem-solving skills to address and solve technical problems that arise as it relates to email campaigns and CRM projects., • Mentor others on coding standards and perform code reviews.Qualifications, • 5+ years of hands-on coding and email production experience within an enterprise level Marketing Automation platforms/Email Service Providers, such as Salesforce Marketing Cloud, Zeta Global, etc., ideally in a B2B/ DTC or other high volume email environment, • Advanced expertise coding in HTML, CSS, and liquid scripting (or AMPscripting) for use in a variety of custom marketing campaigns, • Advanced knowledge in dynamic personalization & audience segmentation, • Understands how to utilize ETL data files and data exchanges, such as JSON, APIs, within Marketing Automation Platforms/ESPs, • Experience with project management tools (JIRA) required, as well as strong project management skills, • Current on the latest email inbox changes, code standards, and industry standards, • Able to work proficiently in an independent and collaborative capacity, • Ability to manage multiple deadline-oriented projects concurrently and thrive in a fast-paced environment, • Excellent verbal and written skills, with proven ability to communicate complex ideas clearly and concisely, • Technical/mathematical aptitude; excellent Excel skills, • Knowledge of debugging techniques and usage of browser developer tools, • Experience in cross-device/browser/OS coding techniques for responsively designed emails, • Ability to use Microsoft applications (Word, PowerPoint, Excel & Outlook) effectively for business purposes. Strong Excel skills are required for this role., • Bachelor’s degree or equivalent combination of education and experience What Sets You Apart • Experience with any versioning control (Git, SVN, Gitlab, Github, Bitbucket, etc), • Exposure to other programming languages (TypeScript, Python, or Rust), • Experience with Figma or has worked directly with UX/UI teams, • Understanding of VML (Vector Markup Language), • Experience in retail, entertainment, sports and/or travel industry is preferred, • Experience using Adobe Analytics, Google Analytics, and other marketing automation platforms, • Understanding of CAN-SPAM and email best practices, • Previous experience as a Front End Developer Salary range : $80k - $90k plus bonus and full benefits. Salary to be determined by multiple factors including but not limited to relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data. EBG uses an Automated Employment Decision Tool in our hiring process for NY positions to evaluate candidates' job-relevant skills and qualifications. The AEDT is in effect beginning March 8, 2025. This tool serves only as one component of our assessment and review process. A human hiring manager or company representative always makes the final hiring decision. Our AEDT has undergone an independent bias audit available for review at AEDT Bias Report . For information about assessment methods accommodations please email TAEBGJobs@ebgsolutions.com. For information about data collection and retention practices, please see our privacy policy at https://ebgsolutions.com/applicant-privacy-policy Additional Information Entertainment Benefits Group offers outstanding employee benefits including: • Medical, Dental & Vision, • 401k Match, • Short Term Disability, Long Term Disability (Company Paid), • Company Paid Basic Life and AD&D, • Additional Voluntary Benefits, • Flexible Work Arrangements, • 3 Weeks of PTO + 5 Personal Days, • Paid Holiday Break from Christmas to New Year, • Paid Holidays, • Fitness Centers (location dependent), • Annual Day of Giving, • Share in the FUN! EBG gives $1000 per year in Tickets-At-Work gift cards to full-time employees to experience and enjoy the savings marketplace! Your information will be kept confidential in accordance with EEO guidelines. The statements contained herein reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required, and the scope of responsibility, but should not be consider an all-inclusive listing of work requirements.

Job Description Software Guidance & Assistance, Inc., (SGA), is searching for a Forward Deployed Engineer (GenAI) for a CONTRACT assignment with one of our premier Financial Services clients in New York, NY. This is a highly embedded, client-facing engineering role. The individual will play a role of Forward Deployed Engineer and will work directly with Fixed Income business users, technology teams, quants, operations, and control functions to identify high-value AI use cases, translate business workflows into technical designs, and build production-grade AI solutions. This role is not advisory. The successful candidate will be expected to sit close to the business, understand front-office and operational workflows, write code, test solutions, debug issues, and help move AI use cases from concept to controlled production adoption. The ideal candidate combines strong software engineering skills, practical generative AI experience, and a consultative approach to working with senior business stakeholders in a regulated financial-services environment. Responsibilities: • Embed with banks Fixed Income teams in New York to understand business workflows, pain points, data availability, and AI opportunities., • Partner with traders, sales, research, operations, risk, compliance, and technology stakeholders to translate business requirements into AI-enabled solutions., • Design, prototype, and build generative AI applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs), prompt engineering, MCP integrations, orchestration, retrieval-augmented generation, and agentic workflows., • Develop AI solutions that support Fixed Income use cases such as knowledge retrieval, workflow automation, document analysis, trade support, client intelligence, operational exception handling, and management reporting., • Build retrieval pipelines across structured and unstructured data, including research, policies, procedures, trade-related data, market commentary, client documents, and internal knowledge repositories., • Apply prompt engineering techniques to improve model accuracy, consistency, explainability, and user trust., • Design evaluation frameworks to test AI outputs for accuracy, completeness, hallucination risk, relevance, and compliance alignment., • Work with technology and control teams to ensure solutions meet enterprise standards for security, data privacy, auditability, access control, and model governance., • Communicate technical trade-offs clearly to both engineering teams and business stakeholders., • Support user adoption by gathering feedback, refining workflows, and ensuring AI tools solve real business problems rather than becoming standalone experiments., • Identify reusable patterns, accelerators, and components that can be scaled across other financial-services use cases. Required Skills:, • Bachelor's degree in computer science, Engineering, Mathematics, Finance, or a related field, or equivalent practical experience., • Strong hands-on experience with Python and modern software engineering practices., • Practical experience building applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs)., • Strong understanding of prompt engineering, including prompt design, prompt testing, grounding, context management, and output validation., • Experience building AI or data-driven applications that use APIs, databases, cloud services, and enterprise data sources., • Ability to work directly with business stakeholders, lead discovery discussions, clarify ambiguous requirements, and convert business problems into technical solutions., • Strong communication skills and the ability to explain AI concepts, risks, and design choices in clear business language., • Experience working in agile, fast-moving environments where prototypes must quickly evolve into production-ready solutions. Preferred Skills:, • Financial-services experience, ideally within capital markets, Fixed Income, trading, sales, risk, operations, or banking technology., • Familiarity with Fixed Income products such as rates, credit, securitised products, municipals, FX, or derivatives., • Experience with retrieval-augmented generation, vector databases, embeddings, semantic search, and document intelligence., • Experience designing AI evaluation frameworks, including test datasets, quality metrics, human review loops, and model performance monitoring., • Familiarity with enterprise AI governance, model risk management, compliance review, data privacy, and regulatory expectations in financial services., • Experience in a forward-deployed, consulting, client engineering, post-sales engineering, or technical delivery role., • Exposure to cloud platforms, secure APIs, authentication/authorisation, and enterprise integration patterns. By applying for a job with SGA, you agree to allow SGA to process your application for this and future opportunities in accordance with our Privacy Policy. Also, to ensure timely processing, you agree to be contacted by our AI recruiter via email, text, or phone. Message frequency varies and data rates may apply, but you can reply STOP to any SMS message to opt-out of texts and may contact SGA at info@sgainc.com to opt-out of AI communications. The choice not to engage with AI will not adversely impact your consideration for placement. AI is not used to make any hiring determinations. SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at https://sgainc.com/ . SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company EEO page to request an accommodation or assistance regarding our policy. #LI-AC1

Job DescriptionPrincipal AI & Knowledge Graph Architect Full Time NYC / NJ area (Hybrid / Telecommute) Our client is currently seeking a Principal AI & Knowledge Graph Architect to join our Information Technology team. The Principal AI & Knowledge Graph Architect will be responsible for leading the technical transformation of engineering standards into intelligent, machine-interpretable digital assets. This role combines expertise across AI systems architecture, knowledge engineering, ontology design, graph technologies, and enterprise-scale digital transformation. It requires balancing innovation with governance ensuring our clients retention of authority, traceability, and control over the digital meaning of its intellectual property. Key responsibilities include: Knowledge Graph & Digital Asset Architecture • Define and own the multi-year strategy and roadmap for Digital Engineering Knowledge Platform., • Drive the integration of standards intelligence into engineering ecosystems, including CAD/CAE, PLM, MBSE, digital twins, and AI-powered engineering tools., • Establish a unified digital platform connecting standards, learning, journals, technical content, APIs, and AI-enabled services., • Explore and operationalize emerging interoperability protocols and frameworks, including MCP, ACP, semantic interoperability standards, and AI orchestration technologies., • Prioritize enterprise platform capabilities and drive scalable growth across business units, content domains, and external standards ecosystems. AI, Semantic Intelligence & Engineering Automation, • Define domain-specific AI architecture strategy, including integration of SLMs, LLMs, RAG pipelines, vector databases, and semantic retrieval frameworks., • Lead architecture for AI-enabled engineering use cases, including:, • Automated compliance validation, • AI-assisted engineering workflows, • Intelligent standards retrieval, • CAD/PLM/MBSE integrations, • AI agent and machine-consumable standards, • Define Human-in-the-Loop (HITL) validation frameworks to ensure trust, technical fidelity, and explainability., • Establish technical guardrails for AI usage, hallucination mitigation, and authoritative engineering interpretation., • Partner with vendors and research organizations to evaluate emerging AI and graph technologies. Governance, Strategy & Enterprise Leadership, • Serve as the senior technical authority for digital knowledge architecture and AI-enabled standards transformation., • Define governance standards for semantic consistency, relationship integrity, validation workflows, and lifecycle management., • Establish architectural and semantic boundaries for external vendors, partners, and AI providers to protect IP and authoritative meaning., • Collaborate with SMEs, Standards leadership, Enterprise Architecture, Legal, Product, and Technology teams to align technical transformation with organizational strategy., • Translate complex AI, semantic, and graph concepts into executive-level guidance, board-ready communication, and strategic recommendations., • Contribute to future-state digital platform strategy, including monetization, APIs, machine-accessible delivery, and multi-SDO interoperability. Demonstrated knowledge in the following areas is required:, • Designing enterprise-scale knowledge graphs, ontologies, semantic models, or AI-enabled information platforms., • Ability to lead complex technical transformation initiatives involving structured and unstructured data., • Experience defining governance and validation frameworks in regulated or technically rigorous domains., • Strong understanding of interoperability standards, APIs, and machine-consumable information architectures., • Ability to operate as a strategic technical leader across executives, SMEs, technology teams, legal stakeholders, and external partners., • Exceptional communication and executive presentation skills. Preferred qualifications include:, • 8+ years of experience in one or more of the following:, • Enterprise Architecture, • AI/ML Systems Architecture, • Knowledge Graphs & Semantic Technologies, • Data & Information Architecture, • Digital Platform Engineering, • Experience with engineering, manufacturing, industrial, or standards-based domains., • Exposure to CAD, PLM, MBSE, simulation, or digital twin ecosystems., • Familiarity with graph databases, ontology frameworks, and semantic standards., • Experience working with AI vendors, research organizations, or emerging technology ecosystems Adam Planica Technology Recruiter PRI Technology P: 973.732.5454 x41 C: 917.572.1363 www.pritechnology.com

Job Description Job Code L2426IT Department Name IT Infrastructure Reports To Director, IT Infrastructure Strategy FLSA Status Exempt Union Code N/A Management Yes About Us: Building Services 32BJ Benefit Funds (“the Funds”) is the umbrella organization responsible for administering Health, Pension, Retirement Savings, Training, and Legal Services benefits to over 185,000 SEIU 32BJ members. Our mission is to make significant contributions to the lives of our members by providing high quality benefits and services. Through our commitment, we embody five core values: Flexibility, Initiative, Respect, Sustainability, and Teamwork (FIRST). By following our core values, employees are open to different and new ways of doing things, take active steps to improve the organization, create an environment of trust and respect, approach their work with the intent of a positive outcome, and work collaboratively with colleagues. The Funds oversees and manages $11 billion of dollars in assets, which are made up of many, varied and complex funds. The dollars come from a number of sources, including the property owners who pay into the funds on behalf of their employees, and as such, requires those who oversee and manage the money to be highly skilled financial management people. 32BJ Benefit Funds will continue to drive innovation, equity, and technology insights to further help the lives of our hard-working members and their families. We use cutting edge technology such as: M365, Dynamics 365 CRM, Dynamics 365 F&O, Azure, AWS, SQL, Snowflake, QlikView, and more. Please take a moment to watch our video to learn more about our culture and contributions to our members: youtu.be/hYNdMGLn19A Job Summary: The Manager, AI Platform & Agentic Orchestration is a hands-on technical leadership role responsible for building, configuring, operating, and governing the infrastructure that enables enterprise AI and agentic capabilities across Building Service 32BJ Benefit Funds (the "Funds"). The position focuses on the technical foundation required to safely deploy AI platforms, agents, models, skills, integrations, guardrails, and related services at scale. Rather than serving primarily as a business-facing solutioning role, this position owns the operational architecture and day-to-day management of the Funds' AI platform environment, including agentic infrastructure, model deployment, skill deployment, MCP server management, configuration standards, access controls, monitoring, usage management, and cost controls. The Manager, AI Platform & Agentic Orchestration works closely with IT Infrastructure, Security, Development, Data Strategy, Data Governance, and Compliance to ensure that AI capabilities can be implemented securely, reliably, and cost-effectively while protecting participant data and maintaining alignment with HIPAA, HITECH, DOL cybersecurity guidance, and internal policies. The role is expected to collaborate with technical and security leaders, including security counterparts such as the Information Security team, to ensure appropriate controls, guardrails, and incident-response practices are built into the AI operating environment. Essential Duties and Responsibilities: • Own the technical configuration, administration, and operational management of the Funds' enterprise AI and agentic infrastructure, including platform settings, environments, integrations, access controls, logging, and monitoring., • Configure and manage agentic AI platforms and operating environments, including an AI-driven Software Development Lifecycle (SDLC) automation platform, ensuring that settings, permissions, guardrails, connectors, and deployment standards are implemented consistently and securely., • Evaluate AI coding and agent tools such as Claude, GitHub Copilot, OpenAI/Codex, and Databricks Genie for use by the organization to address business needs., • Deploy, configure, and maintain AI models, agents, skills, prompts, workflows, and related services across approved enterprise platforms such as Microsoft 365 Copilot, Azure OpenAI, Azure Databricks (Omnigent, Genie), Microsoft Foundry, Claude, and other sanctioned AI tooling., • Manage MCP servers, agent-to-system integrations, API connections, knowledge sources, tool access, and other technical components required to enable secure agentic workflows., • Implement technical guardrails, including role-based access, data-loss-prevention controls, prompt and tool restrictions, model-use boundaries, approval workflows, audit logging, and monitoring alerts., • Establish usage, performance, reliability, and cost-management practices for AI infrastructure, including token consumption, licensing, compute utilization, environment sprawl, and vendor/platform cost controls., • Collaborate with Infrastructure, Development, Security, and Data teams to ensure AI services are deployed within approved technical architectures and integrated appropriately with existing enterprise systems., • Translate AI governance requirements into enforceable technical controls, including platform configuration standards, approved deployment patterns, restricted-use settings, and automated or manual approval checkpoints., • Develop and maintain enterprise AI technical standards and reference architectures; participate in AI architecture reviews and the AI Center of Excellence; and contribute to the enterprise AI technology roadmap., • Maintain the technical AI inventory, and lifecycle of deployed models, agents, prompts, skills, MCP servers, connectors, knowledge sources, integrations, and environments, including owners, access levels, versioning, monitoring, change management, retirement, and cost profiles., • Conduct or support pre-deployment technical risk reviews focused on PHI/ePHI exposure, data residency, storage and retention, system integration risk, model/tool access, logging, auditability, and controls against prompt injection, data leakage, and unauthorized tool use., • Operationalize the Funds' AI Tool Vetting and Approval process, administering the intake queue, applying the risk-tiered classification model (Low / Medium / High / Prohibited), and routing requests for appropriate review. Low request items will be deployed without further review., • Partner with Information Security, the vCISO, and Compliance to ensure AI infrastructure aligns with cybersecurity standards, incident-response processes, HIPAA/HITECH requirements, and the Funds' internal control environment., • Support evaluation of third-party AI platforms and infrastructure components, including technical security requirements, data-use terms, model training restrictions, retention practices, logging capabilities, breach-notification obligations, and integration risks., • Monitor deployed AI services for unauthorized data exposure, policy violations, cost anomalies, model or agent misuse, integration failures, and drift from approved technical configurations., • Document control decisions, configuration standards, mitigation requirements, exceptions, and remediation plans in coordination with governance, security, and infrastructure leadership., • Develop and maintain technical standards, runbooks, deployment procedures, configuration checklists, and operating practices for AI platforms, agents, models, skills, MCP servers, and related services., • Produce operational dashboards and reports covering usage, licensing, infrastructure cost, token or compute consumption, platform utilization, deployed agents and skills, open risks, exceptions, and remediation status., • Serve as the technical implementation lead for AI infrastructure initiatives, ensuring the Funds has the platform capacity, controls, and deployment mechanisms needed to support a growing portfolio of AI projects., • Partner with business-facing teams as needed to understand implementation requirements, while keeping primary accountability for the technical environment, deployment architecture, and operational controls., • Partner with Enterprise Architecture to ensure AI platforms, services, and integrations align with enterprise technology standards and architecture., • Participate in AI governance discussions by providing technical feasibility assessments, infrastructure readiness updates, cost implications, control recommendations, and implementation constraints., • Stay current on emerging AI platform architectures, agentic infrastructure patterns, MCP standards, AI security controls, and responsible deployment practices, ensuring the Funds' technical environment remains secure and scalable., • Perform other duties as assigned by management., • Provide support outside of regular working hours and on weekends. Qualifications (Competencies): • 5+ years of experience in IT infrastructure, cloud engineering, platform administration, systems integration, DevOps, cybersecurity, data platforms, or enterprise technology operations., • Hands-on experience deploying, configuring, operating, or securing enterprise AI, automation, cloud, integration, or data platforms is strongly preferred., • Experience with vendor/platform management, technical security reviews, operational monitoring, cost management, and production support practices., • Healthcare, benefits administration, HIPAA-regulated, or highly regulated enterprise experience preferred., • Strong hands-on technical knowledge of enterprise AI platforms, generative AI services, agentic architectures, model deployment patterns, skill deployment, API integrations, and secure platform operations., • Working knowledge of AI/ML concepts and AI-specific risks, including prompt injection, data leakage, unauthorized tool use, model drift, hallucination risk, explainability, and output reliability., • Experience configuring and operating AI platforms, cloud-based AI services, Microsoft 365 Copilot, Azure OpenAI, MCP servers, agent frameworks, or comparable enterprise AI infrastructure., • Working knowledge of prompt engineering and versioning, model and prompt lifecycle management, agent orchestration, MCP architecture, RAG and vector technologies, AI evaluation and observability, Git/version control, APIs, Python, Azure AI Foundry/Azure OpenAI, and AI governance and guardrail technologies., • Strong understanding of cybersecurity, access controls, logging, monitoring, incident response, data-loss prevention, and secure integration practices., • Understanding of data privacy and regulatory compliance requirements, particularly HIPAA and HITECH, as well as familiarity with DOL cybersecurity guidance and emerging AI governance expectations., • Ability to manage AI infrastructure costs, licensing, token/compute consumption, utilization reporting, vendor/platform usage, and environment governance., • Demonstrated ability to create technical standards, runbooks, configuration documentation, operating procedures, and deployment controls., • Strong collaboration skills with technical infrastructure, development, security, compliance, privacy, and data governance stakeholders., • Clear communication skills, with the ability to explain technical risks, controls, costs, and implementation requirements to both technical and non-technical stakeholders., • AI platform administration and agentic infrastructure operations., • Model, agent, skill, and MCP server deployment., • Technical guardrails, access controls, and secure configuration management., • AI infrastructure monitoring, usage reporting, and cost management., • Cybersecurity, privacy, and compliance alignment, including HIPAA/HITECH., • Technical documentation, runbooks, deployment standards, and operational discipline., • Vendor/platform evaluation and third-party technical risk review., • Collaboration with infrastructure, development, security, compliance, and data governance teams., • Problem-solving, systems thinking, and implementation-focused execution. Soft Skills (Interpersonal Skills): • Detail oriented with excellent organization and analytical skills., • Ability to plan, take initiatives to accomplish objectives in a timely fashion, and work independently., • Ability to prioritize work and meet deadlines., • Ability to establish and maintain effective working relationships with project team members, supervisors, and other employees. Education: Bachelor's degree in Information Technology, Computer Science, Cybersecurity, Data Engineering, Cloud Engineering, or a related technical field; relevant certifications or a Master's degree preferred. Language Skills: Speak, read, write and understand English Reasoning Ability: High Certificates, Licenses, Registrations: Certifications such as Microsoft Azure Administrator, Azure AI Engineer, Azure Security Engineer, CISSP, CISM, CRISC, cloud architecture, DevOps, cybersecurity, or AI governance/responsible-AI credentials are beneficial. Project-management certification is a plus but not required. Shift Standard business hours, with after-hours, weekend, and on-call support as required. <

Job Description Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team. Job Title: AI Senior Security Engineer Location(s): Jersey City, NJ, Tampa, FL or Phoenix AZ Job Summary Seeking a highly motivated Security Engineer to design, develop, and deploy autonomous AI agents that reduce manual overhead and drive intelligent decision-making across cybersecurity operations while ensuring appropriate guardrails, security controls, data privacy, and human oversight. Key Responsibilities • Design, build, and maintain AI agents capable of multi-step reasoning and tool use to automate cybersecurity use cases, including autonomous incident investigation and vulnerability prioritization., • Develop advanced prompt engineering solutions using high-precision, version-controlled prompts and programmatic techniques to optimize LLM outputs for reliable security logic and automated remediation., • Use and fine-tune machine learning models, including deep learning, K-Means, SVM, and related techniques, to identify sophisticated attack patterns that bypass traditional signature-based defenses., • Integrate large language models from providers such as OpenAI, Anthropic, and open-source platforms into production environments through APIs or local deployments., • Develop and optimize data ingestion pipelines, with a particular focus on vector databases and AI-ready data processing., • Audit existing manual workflows and re-engineer them using a machine-first approach, leveraging LLMs to process and analyze unstructured data., • Deploy, monitor, and optimize AI solutions using cloud-native technologies, ensuring high availability, low latency, scalability, and cost efficiency., • Implement AI safety and security guardrails to ensure appropriate outputs, ethical standards, data privacy, and human-in-the-loop checkpoints where required. Required Qualifications • Hands-on experience with Python, including data ingestion, data cleaning, machine learning libraries, and system and web-based integrations., • Proficiency with machine learning frameworks and libraries, preferably Scikit-Learn and PyTorch., • Experience with AI agent orchestration frameworks such as LangChain, CrewAI, or AutoGPT., • Hands-on experience developing and tuning machine learning models for a range of cybersecurity use cases., • 3–4 years of hands-on experience with at least one cloud-based AI platform, such as AWS Bedrock, AWS SageMaker, or Azure AI., • Experience with Docker, Kubernetes, and Git for deployment and version control., • Strong experience with RESTful and GraphQL APIs for integrating disparate systems., • Experience designing and implementing AI/ML solutions in cybersecurity environments. Education • Bachelor's or Master's degree in Cybersecurity, Computer Science, Artificial Intelligence, or a related field., • Relevant industry certifications and equivalent practical work experience may be considered. Preferred Certifications • GIAC Machine Learning Engineer, • AWS Certified Machine Learning Engineer, • Microsoft Certified: Azure AI Engineer Associate, • Certified Information Systems Security Professional (CISSP) Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.

Job DescriptionDescription: AI Cloud Engineer - RTH Location: Hybrid | Experience: 3-5 years | Function: AI Engineering & Cloud Platforms ABOUT THE ROLE We are seeking a GenAI Cloud Engineer to build and deploy enterprise-scale agentic AI solutions that support complex business workflows, decision support, operational intelligence, customer engagement, and other signal-to-action use cases across the enterprise. This is a hands-on engineering role responsible for designing, developing, and delivering production-grade AI agents using AWS Bedrock, Amazon Bedrock AgentCore, enterprise data products, semantic layers, and governed cloud-native architectures. You will implement agent runtimes, orchestration patterns, memory, tool integration, observability, evaluation, and guardrail capabilities while partnering with architects, data teams, product owners, and Responsible AI stakeholders. The ideal candidate has recent experience building enterprise agents, agentic RAG, multi-agent workflows, and secure integrations with business systems in regulated environments. KEY RESPONSIBILITIES Develop cloud-native microservices, APIs, and event-driven components using Python, JavaScript/TypeScript, FastAPI, AWS Lambda, EventBridge, and related AWS services. Build and deploy enterprise AI agents using Amazon Bedrock AgentCore, Bedrock models, AgentCore runtime services, AgentCore Gateway, agent registry patterns, and agent-to-agent communication where appropriate. Implement data ingestion, semantic retrieval, embeddings, vector search, knowledge graph, and memory pipelines that allow agents to consume certified data products, Denodo/USBIE sources, Bedrock Knowledge Bases, and governed enterprise content. Develop intent classification, tool routing, workflow orchestration, guardrails, policy checks, human-in-the-loop controls, and fail-safe escalation patterns for agentic applications. Integrate agents with enterprise systems and workflows such as Salesforce/Elevate, Service Platform, CaseView, Genesys, MAC/MPI, USBIE, Denodo, APIs, MCP tools, and event streams. Build evaluation, monitoring, tracing, and operational controls for agents, including quality metrics, hallucination and safety checks, latency, cost, feedback loops, and incident response readiness. Uphold enterprise standards for application security, IAM/agent identity, data protection, auditability, Responsible AI, ADS/data-product governance, observability, and production reliability. Stay current with AWS AgentCore, Bedrock, agent frameworks, model evaluation approaches, memory architectures, semantic data products, and enterprise agentic AI patterns. LEADERSHIP, MENTORING & INFLUENCE (ONLY FOR SENIOR 5-8 YEARS OF EXPERIENCE) Lead a workstream: Take technical ownership of a defined feature area or service - from design through production support - coordinating a small group of engineers where needed. Mentor engineers: Guide associate and mid-level engineers through code review, pairing, and design feedback; help them build GenAI and cloud skills. Contribute to architecture: Participate actively in design reviews, propose solution options with clear trade-offs, and help shape the patterns and standards the team adopts. Influence through delivery: Partner directly with product owners, architects, and business stakeholders to refine requirements and build credibility through working software. Improve the team: Identify and drive improvements in engineering practices, tooling, reusable components, and documentation; share knowledge through demos and internal write-ups. REQUIRED QUALIFICATIONS 3-5 years of software engineering experience, with hands-on delivery of cloud-native applications or AI/ML-enabled platforms. Strong proficiency in Python and JavaScript/TypeScript, including API development, asynchronous processing, test automation, and production debugging. Experience developing microservices, APIs, event-driven workflows, distributed applications, and secure integrations with enterprise systems. Hands-on experience with AWS cloud services, including serverless, container, messaging/eventing, IAM, observability, and cloud-native deployment patterns. Recent experience building enterprise GenAI or agentic AI solutions, including agents, agentic RAG, multi-step orchestration, chat experiences, or signal-to-action workflows. Experience with Amazon Bedrock, Amazon Bedrock AgentCore, or comparable enterprise LLM and agent runtime platforms. Experience with LangGraph, LangChain, Strands, MCP, A2A protocols, tool-use frameworks, or comparable multi-agent orchestration patterns. Experience with model evaluation, prompt engineering, agent quality testing, feedback loops, LLM-as-judge patterns, and reliability measurement. Experience with data ingestion, vector databases, embeddings, semantic search, knowledge bases, memory stores, and retrieval patterns for structured and unstructured data. Experience implementing AI guardrails, safety controls, intent classification, routing logic, access controls, audit logging, evaluation, and human escalation paths. Strong understanding of software engineering best practices, application security, Responsible AI expectations, data governance, scalability, resilience, and production operations. Experience mentoring engineers, leading technical delivery of a defined workstream, and collaborating with architects, product owners, data teams, and platform teams. PREFERRED QUALIFICATIONS Experience with event-driven and serverless architectures using AWS EventBridge, MSK, SNS/SQS, Step Functions, Lambda, API Gateway, and container services. Experience delivering AI or data products in financial services, insurance, or other regulated environments with privacy, compliance, audit, and control requirements. Familiarity with enterprise data products, semantic layers, Denodo, USBIE, ADS certification, knowledge graphs, Neptune/OpenSearch, and governed data consumption patterns. Experience integrating agents with CRM, service, telephony, document, workflow, or engagement platforms such as Salesforce, Genesys, Service Platform, MAC/MPI, or similar systems. IDEAL CANDIDATE You are a strong software engineer with recent enterprise GenAI and agentic AI experience who enjoys turning ambiguous business use cases into reliable, governed, production-ready agents. You understand that CNS agents must combine data products, signals, deterministic rules, LLM reasoning, memory, tool use, observability, and human controls. You can work across cloud architecture, data integration, AI orchestration, and production operations while raising the technical bar for the team. LEVELING: SENIOR VS. DEV Senior GenAI Cloud Engineer - 5–8 years. Owns architecture and technical direction for enterprise agentic AI capabilities, sets standards for AgentCore, data, governance, observability, and multi-agent patterns, leads complex multi-team initiatives, mentors senior engineers, and influences cross-team design decisions. GenAI Cloud Engineer - 3+ years. Hands-on technical contributor. Leads implementation of specific agent workstreams, contributes to AgentCore architecture and delivery patterns, mentors associate and mid-level engineers, and influences within the team through working software. Rate: $60-65/hr #LI-PP1

Job DescriptionCompany Description Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. Sia’s AI & Data Business Unit is the powerhouse of our firm’s innovation—merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia’s AI & Data team, you’ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. Job Description We are growing our Generative AI consulting practice and looking for motivated recent graduates to join as GenAI Consultants. You'll work at the intersection of cutting-edge AI and real business problems — helping clients across industries design, build, and deploy LLM-powered solutions that create tangible value. This is a hands-on technical role. You'll contribute to the full lifecycle of GenAI projects: from architecture and prototyping through to production deployment, evaluation, and iteration. We invest heavily in your development, and expect you to do the same. What You'll Do You'll design and implement GenAI/LLM solutions leveraging models such as Claude, GPT, Gemini, Llama, and Mistral — selecting the right approach (RAG, agents, fine-tuning, prompt engineering) for each client context. You'll support senior architects in designing scalable, secure, and compliant AI applications while building hands-on experience across the full stack. Responsibilities • LLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques., • Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications., • Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.)., • Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions., • RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution)., • Model Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities., • Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP)., • Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes., • Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing., • Collaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical)., • Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference., • Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). Qualifications, • Bachelors Degree Required, • Recent graduate (within 2 years) in CS, Engineering, Data Science, or equivalent, • Strong Python programming skills, • Familiarity with at least one GenAI framework (LangChain, LlamaIndex, or similar), • Foundational knowledge of NLP concepts, vector embeddings, and semantic search, • Exposure to cloud platforms (AWS, Azure, or GCP), • Ability to explain technical concepts clearly to diverse audiences Claude Certified Architect (CCA) Requirement All candidates must hold — or demonstrate the clear ability to obtain within one week of hire — the Claude Certified Architect – Foundations (CCA-F) certification from Anthropic. Preferred Qualifications • Masters Degree Preferred, • Prior experience building agentic AI systems (LangGraph, AutoGen, etc), • Familiarity with vector databases (Pinecone, Chroma, pgvector, OpenSearch), • Experience with or understanding of the Model Context Protocol (MCP), • Hands-on fine-tuning experience with open-source LLMs, • Familiarity with Docker, Git, and CI/CD workflows Additional Information Compensation & Benefits We believe in supporting our team professionally and personally. Here’s a snapshot of the comprehensive benefits you’ll enjoy as part of Sia. Competitive Compensation • Annual Base Salary Range: $80,000-110,000 annually, commensurate with experience and qualifications, • Annual performance based discretionary bonus Robust Health Coverage • 3 Medical plans, • Dental and Vision, • Life, AD&D and other voluntary insurance Tax-Advantaged Accounts • 401K retirement plan, • 4% matching and 100% vested upon enrollment, • Health Savings Account (HSA), • Flexible Spending Account (FSA), • Health, Dependent Care, Commuter Family Friendly Benefits • 100% paid parental leave for all new parents with eligible tenure, • Building Healthy Families program if enrolled through Medical plan Time Off to Recharge • Generous Paid Time Off (PTO) policy, • 9 company holidays plus 1 floating holiday Extras that Make Life Easier • College savings and student loan repayment assistance, • Monthly cell phone stipend, • Access to wellness programs at no cost if enrolled through Medical plan, including:, • Employee Assistance Program at no cost Diversity, Equity, Inclusion & Belonging At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. Office Workplace Guidelines Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco—are expected to live within a reasonable commuting distance and attend the office at least three days or more per week. For Consultants outside of our primary markets, we can offer more flexible in-person requirements in accordance with your location. Work Authorization & Sponsorship At this time, Sia does not intend to employ any applicant who will require, either now or in the future, employment visa sponsorship or sponsorship for work authorization (i.e., H1-B visa, F-1/OPT) or STEM OPT, TN, etc). Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

Job Description Join Tech @ Ro to build the future of healthcare, from the ground up! At Ro, we believe that when people achieve their health goals, they can achieve their life goals. The highest-leverage way to move society forward is to give people their health, and the current healthcare system isn’t built to do that. It was built to bill, not to serve patients. We’re building a new system. One where the patient is in control. One designed from scratch for the digital age. At Ro, technology isn’t just a function… It's core to how we deliver care. We’ve built a vertically integrated healthcare platform that connects telehealth, diagnostics, pharmacy, and logistics into a seamless, end-to-end experience for millions of patients. …and we’re just getting started. As part of Tech @ Ro, you’ll work on systems that operate at scale, with an opportunity to: • Solve complex, high-concurrency problems across a full-stack platform, • Build and ship quickly with tight feedback loops and real-world impact, • Own systems end-to-end, from architecture to production performance, • Work alongside experienced operators, technical leaders, and clinicians, • Help define how modern healthcare should be delivered We’re a performance-driven team with a strong sense of ownership and urgency. We move fast, learn quickly, and hold a high bar for what we build, and do so with a big heart — because patients depend on it. If you’re motivated by impact, scale, and the chance to help lead the patient revolution, come build with us. The Role Ro is building a team focused on shipping LLM-powered products across the patient experience, clinical operations, and internal tooling. We're hiring a Senior Engineer, Applied AI to join a new team we’re building from the ground up alongside a Senior AI Lead and an Engineering Manager. You'll own AI features from prototype through production and spend as much time improving workflows with clinical operators as writing code. Most of your work will involve building orchestration layers, prompts, evaluations, retrieval systems, and tooling that make LLMs reliable enough for real-world healthcare operations. What You'll Do • Design, build, and ship production LLM powered features end-to-end., • Build the AI application layer, including prompt orchestration, tool calling, retrieval (RAG), embeddings, agent workflows, and structured outputs., • Develop evaluation infrastructure, including regression suites, LLM-as-a-judge evaluations, synthetic datasets, human review workflows, and quality metrics that catch regressions before users do., • Design observability systems that measure accuracy, latency, cost, hallucination rates, and model behavior in production., • Build safety and reliability guardrails that ensure AI systems meet quality, compliance, and operational requirements., • Evaluate and integrate third-party tools, including orchestration frameworks, evaluation platforms, vector databases, and model providers; and make pragmatic build-versus-buy decisions., • Raise engineering standards across the team through technical leadership, code reviews, mentorship, and thoughtful system design., • Sit with EHR operators, Patient Advocates, and clinical teams to understand the workflows you're automating., • Prototype quickly, ship early, measure outcomes, and iterate based on real-world usage.What You’ll Bring to the Team, • 5+ years building production software, with at least 1–2 years building and deploying LLM-powered applications in production (or equivalent depth through substantial side projects or open-source work)., • Strong Python engineer with experience building backend services and integrating modern AI APIs and frameworks., • Comfortable using AI-assisted development tools throughout the software development lifecycle., • You've shipped AI features that served real users, and you can clearly articulate how you measured quality, reliability, latency, cost, and business impact., • You have strong product instincts and thrive in ambiguous environments, translating operational problems into technical solutions without relying on detailed specifications., • Bonus: Experience with orchestration frameworks (LangChain, LangGraph, AgentCore), RAG architectures, vector databases, prompt/version management, and evaluation or observability platforms (e.g., LangSmith, Braintrust, Arize Phoenix). A note on reporting structure This is a new function at Ro, and we're being deliberate about not over-defining it. Your manager and where you sit on the org chart will depend on the specific shape of the team we end up with. We'd rather find the right people and figure out the lines around them than pre-draw boxes and miss great candidates. If that ambiguity is a deal-breaker, this isn't the right role; if it sounds like an opportunity, we want to talk. • The target base salary for this position ranges from $190,800 to $234,500 in addition to a competitive equity and benefits package (as applicable). When determining compensation, we analyze and carefully consider several factors, including location, job-related knowledge, skills and experience. These considerations may cause your compensation to vary. Ro is consistently recognized as a top workplace in Health Care, in New York, and for Women and Parents—earning more than 20 honors from Fortune, Great Place to Work, and PEOPLE since 2021. In 2025 alone, we ranked top 5 among medium workplaces in Health Care and New York, and top 50 nationwide. At Ro, we believe that our diverse perspectives are our biggest strengths — and that embracing them will create real change in healthcare. As an equal opportunity employer, we provide equal opportunity in all aspects of employment, including recruiting, hiring, compensation, training and promotion, termination, and any other terms and conditions of employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, familial status, age, disability and/or any other legally protected classification protected by federal, state, or local law. Ro is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and interview process. If you require a reasonable accommodation in the application or interview process, please contact us at talent@ro.co. See our California Privacy Policy here. We may use automated tools, including artificial intelligence (AI), to assist with parts of our recruiting and hiring process, such as reviewing applications, evaluating resumes, and assessing responses or job-related qualifications. These tools are used to support our recruitment team and do not replace human judgment. Final hiring decisions are made by humans.

Senior Software Engineer (TypeScript / React / LLM Systems) • AI Infrastructure • $250,000 • Hybrid (2 days/week) • New York, NY Must be based in NYC & the role requires US Citizenship due to regulatory constraints. No sponsorship/visas/Green Card. About the Role We’re hiring a Senior Software Engineer to help build production-grade LLM-powered systems used in high-impact, real-world workflows. This is a true SWE + ML role. You’ll sit at the intersection of frontend UX, backend systems, and applied machine learning - owning features end to end. That includes React-heavy user interfaces, TypeScript services, and the pipelines that power LLM reasoning, retrieval and fine-tuning behind the scenes. You’ll work closely with product, design and ML engineers to ship tools where reliability, clarity and user experience matter just as much as model quality. Why You’ll Love It: Own real systems: From UX flows to LLM pipelines running in production. Engineering-first culture: Practical ML, not research theatre. Everything ships. High-impact UX: Build interfaces used daily by technical and non-technical users. Move fast: Small teams, short cycles, minimal process overhead. Serious problems: Latency, hallucination control, evaluation, observability and scale. What You’ll Do • Design and build TypeScript services that power LLM workflows including RAG pipelines, prompt orchestration and fine-tuning flows., • Develop rich, intuitive React interfaces for AI-driven products - heavy focus on UX, clarity and usability., • Implement retrieval systems using vector databases, hybrid search and structured data sources., • Work hands-on with LLM APIs and open-source models (OpenAI, Anthropic, open-weight models)., • Collaborate with ML engineers on evaluation, fine-tuning strategies and production rollout., • Own backend architecture across Node.js services, async pipelines and model-facing APIs., • Improve system reliability through logging, monitoring, tracing and failure handling., • Mentor engineers and contribute to design and architecture decisions across the platform. Tech Stack Frontend: React, TypeScript, Next.js, Tailwind CSS, Storybook Backend: Node.js, TypeScript, REST, GraphQL LLM Systems: RAG pipelines, fine-tuning workflows, prompt orchestration Data & Retrieval: PostgreSQL, Vector DBs (Pinecone, Weaviate, pgvector), Redis Infrastructure: AWS, Docker, Kubernetes, Terraform Observability: OpenTelemetry, Prometheus, Grafana, Sentry Nice to Have • Experience building production LLM systems beyond prototypes, • Hands-on fine-tuning experience (LoRA, adapters, evaluation pipelines), • Background in ML engineering or applied NLP, • Experience designing complex frontend UX for data-heavy or AI-driven products, • Familiarity with model evaluation, guardrails and hallucination mitigation Interview Process • Intro Call with Open Talent (30 mins), • Technical Deep-Dive (TypeScript / React + LLM systems, 60 mins), • System Design & Architecture (45 mins), • Leadership Chat with CTO (30 mins) → Offer What We Offer Comp: $160K-$250K W-2 (+ meaningful equity) Benefits: Health, dental, vision, 401(k) Time Off: Flexible PTO + company holidays Growth: Conference budget, learning allowance Environment: Hybrid (2 days NYC office), flexible notice period Equal Opportunity We're hiring for an Equal Opportunity Employer. Due to strong market interest, please apply early or email sufy@opentalent.uk to avoid missing out. All NYC roles posted here first: linkedin.com/in/sufyanbashir/

Role: AI Solution Architect \n Location: Manhattan, NY (NY/ NJ talents are preferred) \n Full time permanent \n \n We are looking for an experienced AI Solution Architect to architect and deliver enterprise-grade AI/ML, Generative AI, and Agentic AI solutions using Spec-Driven Engineering practices. The role requires a combination of strong architecture expertise, hands-on AI engineering knowledge, cloud-native solution design, and the ability to translate complex business requirements into secure, scalable, production-ready AI solutions through clear, testable, and traceable specifications. \n \n Required Skills \n\n • Strong understanding of Machine Learning, Deep Learning, Generative AI, LLMs/SLMs, RAG, Agentic AI, prompt/context engineering, embeddings, vector search, structured outputs, and AI evaluation techniques.\n, • Strong hands-on knowledge of Python and AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or CrewAI.\n, • Experience with enterprise AI and cloud platforms such as Azure AI Foundry/Azure Machine Learning, AWS SageMaker and related AWS AI services, or Google Vertex AI.\n, • Knowledge of SQL, NoSQL, vector databases, graph databases, knowledge graphs, and data/platform technologies such as Kafka, Spark, and Airflow.\n, • Experience with cloud-native engineering and MLOps/LLMOps, including Docker, Kubernetes, Terraform, CI/CD, GitOps, MLflow or equivalent lifecycle and observability platforms.\n, • Strong understanding of REST/GraphQL APIs, microservices, event-driven architectures, distributed systems, enterprise integration patterns, and architecture for security, privacy, resiliency, scalability, performance, observability, and cost optimization.\n, • Experience with Spec-Driven Engineering, including requirements decomposition, architecture and API specifications, executable acceptance criteria, specification-to-code/test traceability, version control, and AI-assisted engineering workflows.\n, • Strong client-facing solutioning, stakeholder management, technical leadership, architecture documentation, and communication skills, with experience designing AI solutions for regulated industries.\n, • Knowledge of knowledge graphs, ontologies and Graph-RAG architectures\n\n \n Key Responsibilities \n\n • Architect end-to-end enterprise AI solutions spanning data ingestion, model/LLM integration, retrieval, orchestration, application integration, deployment, evaluation, monitoring, and governance.\n, • Design Generative AI, RAG, and Agentic AI solutions.\n, • Define Agentic AI architectures incorporating agent orchestration, tool/API integration, context and memory management, human-in-the-loop controls, guardrails, evaluation, and observability.\n, • Evaluate and select appropriate LLMs, SLMs, embedding models, AI frameworks, retrieval approaches, and deployment patterns based on accuracy, latency, security, scalability, and cost.\n, • Architect AI solutions using services across AWS, Microsoft Azure, and Google Cloud, with deep expertise in at least one hyperscaler.\n, • Design cloud-native and distributed architectures using APIs, microservices, event-driven patterns, containers, and Kubernetes.\n, • Define enterprise AI security and governance controls covering identity and access, data privacy, responsible AI, model security, auditability, and regulatory requirements.\n, • Lead solution discovery, architecture definition, technical assessments, POCs, reference architectures, reusable accelerators, and productionization.\n, • Drive Spec-Driven Engineering across the AI solution lifecycle by translating business intent, architecture decisions, functional and non-functional requirements, interfaces, guardrails, and acceptance criteria into version-controlled, machine-consumable specifications that guide design, code generation, testing, validation, and deployment.\n, • Partner with business stakeholders, enterprise architects, product teams, data scientists, AI engineers, DevOps/platform teams, and security teams.\n, • Provide technical leadership, conduct architecture/design reviews, mentor engineering teams, and communicate solution trade-offs to technical and executive stakeholders.\n\n

Based in Los Angeles, New York or Washington, D.C., the Director Of Data Services will be responsible for managing the way Gibson Dunn captures, governs, integrates, and activates its data across every financial system, matter, client relationship, and AI model that the firm deploys. This role will establish the data foundation upon which the firm's AI program, business intelligence capability, and operational decision-making rest. This executive-level role will build the firm's first enterprise-grade data architecture, create a lasting data governance culture, and deliver analytics products that give firm leadership and practice group heads a level of strategic intelligence the firm has never had before. This role reports to the Chief Legal Operations Officer. Responsibilities include: • Owning and continuously evolving the firm's enterprise data strategy and multi-year roadmap approved by firm leadership, integrating with the AI strategy, and aligning to the firm's financial, operational, and competitive priorities., • Advising the CLOO on data's strategic implications including: the value of data assets the firm already holds, the investments required to realize that value, and the risks of continued data fragmentation., • Establishing Gibson Dunn's data vision by articulating what the firm's data estate will look like at full maturity, what decisions it will enable, and how it will position the firm competitively., • Building and chairing the firm's Data Governance Council., • Leading annual data strategy reviews with firm leadership presenting progress, ROI, and updated priorities against the multi-year roadmap., • Designing and overseeing the build of the firm's enterprise data architecture, creating a unified, governed data layer integrating Aderant (financial/billing), iManage (document management), Intapp (conflicts, NBI, risk), CRM, HR systems, and operational platforms., • Leading the selection and implementation of modern data infrastructure tools and platforms including cloud data warehouse (Snowflake, Databricks, Azure Synapse, or equivalent), ETL/ELT orchestration, data catalog, and lineage tooling., • Establishing and enforcing enterprise data standards, taxonomies, and metadata policies, resolving the multi-definition problem affecting key firm metrics such as realization rate, utilization, and client revenue., • Owning the firm's master data management (MDM) program, establishing authoritative systems of record for clients, matters, attorneys, rates, and timekeeper hierarchy., • Overseeing the data engineering team and setting technical standards for pipeline development, data quality testing, schema design, and system integration architecture., • Owning a Practice Intelligence platform providing firm leadership, practice group co-chairs, and administrative leaders with self-serve access to matter pipelines, utilization, realization, client revenue, lateral productivity, and workforce analytics., • Partnering with Finance to deliver analytics beyond standard reports, providing partner-level, matter-level, and client-level economic insight that informs compensation, pricing, and staffing decisions., • Partnering with Business Development to build client intelligence products including relationship analytics, cross-sell opportunity modeling, client revenue trend analysis, and competitive positioning data., • Partnering with Human Resources to provide workforce analytics including staffing models, associate advancement tracking, DEI reporting, and lateral hiring ROI analysis., • Establishing a BI Center of Excellence, selecting, governing, and supporting firm BI and visualization tooling (Power BI, Tableau, or equivalent); building a community of data users; and expanding self-serve analytics capability across the firm., • Developing and owning the firm's comprehensive Data Governance Policy, covering data ownership, access controls, classification, retention, lineage, quality standards, and AI training eligibility, reviewed and approved by firm leadership, IT Security, and General Counsel., • Managing the firm-wide Data Stewardship Program., • Working with OGC, ensure all data practices comply with GDPR, CCPA, applicable bar confidentiality rules, client contractual data obligations, and the firm's information security policies; serving as the firm's data compliance authority., • Representing the firm's data interests in enterprise technology decisions, ensuring architecture, security, and governance requirements are built into every major system procurement., • Serving as an essential executive business partner on AI infrastructure: owning the data layer that powers all firm AI programs, including retrieval-augmented generation pipelines, vector databases, embedding workflows, and the knowledge retrieval infrastructure attorneys use to surface precedents and work product., • Defining and enforcing data quality, classification, and access-control standards governing which firm data is eligible for AI retrieval, training, or fine-tuning, ensuring all AI use of firm data meets confidentiality, privilege, and security requirements., • Building and maintaining AI-ready data infrastructure at the pace the AI Team program requires, coordinating with IT to remove data blockers for every AI deployment., • Owning the firm's data audit logging infrastructure (Harmonic) for AI tools, ensuring complete, auditable records of what data AI tools accessed, when, and by whom., • Building, leading, and developing a high-performing organization of professionals across data governance, analytics, records, and governance, with deep commitment to talent development and succession planning., • Serving as an executive sponsor for data literacy and data culture initiatives across the firm, demonstrating personally that data-driven decision making is how Gibson Dunn's leadership operates., • Maintaining a strong external network with data leaders in professional services, technology, and financial services to continuously benchmark the firm's data maturity and import relevant innovations. Qualifications: • 15+ years of progressive experience in data engineering, data architecture, analytics, or enterprise data strategy; at least 5 years in a Director, VP, or executive director-level role., • Proven track record building enterprise data infrastructure from the ground up in a complex, multi-system environment, including data warehouse architecture, ETL/ELT pipeline development, and enterprise data governance., • Deep expertise in modern data stack technologies: cloud data warehouses (Snowflake, Azure or equivalent), orchestration tools, data catalog and lineage platforms, and BI visualization tooling., • Proven experience developing and implementing data governance frameworks that achieve lasting organizational adoption, including data ownership models, classification schemas, and stewardship programs., • Exceptional executive presence: ability to translate data complexity into strategic insight for partners, managing partners, and peers., • Strong track record building and leading multidisciplinary data organizations spanning engineering, analytics, and governance., • Professional services, legal, financial services, or other highly regulated, data-sensitive industry experience. Experience: • Prior experience at a law firm, in-house legal department, or legal technology company., • Familiarity with legal systems: Aderant (financial/billing), iManage (DMS), Intapp (conflicts/risk/NBI), or comparable platforms., • Experience building AI data infrastructure: RAG pipelines, vector databases, embedding workflows, and LLM evaluation data architectures., • Understanding of attorney-client privilege, confidentiality rules, and professional responsibility as applied to data management and AI., • Experience with master data management (MDM) in a multi-entity, multi-jurisdictional environment., • Advanced degree in Data Science, Computer Science, Information Management, Statistics, or related field; or JD/MBA with strong quantitative background., • Professional certifications in data governance, architecture, or cloud platforms (CDMP, TOGAF, Snowflake SnowPro, AWS/Azure data certifications). Gibson Dunn will consider for employment qualified Applicants with Criminal Histories in a manner consistent with the requirements of local law. Compensation & Benefits: The annual compensation range for this position is $300k 380k. The salary offered within this range will depend upon qualifications and other operational considerations. Benefits offered for this position include health care; retirement benefits; paid days off, including sick time, and vacation time; parental leave; basic life insurance; Flexible Spending Accounts; as well as discretionary, performance-based bonuses.

Role: AI Solution Architect \n Location: Manhattan, NY (NY/ NJ talents are preferred) \n Job Type: Full time permanent \n \n We are looking for an experienced AI Solution Architect to architect and deliver enterprise-grade AI/ML, Generative AI, and Agentic AI solutions using Spec-Driven Engineering practices. The role requires a combination of strong architecture expertise, hands-on AI engineering knowledge, cloud-native solution design, and the ability to translate complex business requirements into secure, scalable, production-ready AI solutions through clear, testable, and traceable specifications. \n \n Required Skills \n\n • Strong understanding of Machine Learning, Deep Learning, Generative AI, LLMs/SLMs, RAG, Agentic AI, prompt/context engineering, embeddings, vector search, structured outputs, and AI evaluation techniques.\n, • Strong hands-on knowledge of Python and AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or CrewAI.\n, • Experience with enterprise AI and cloud platforms such as Azure AI Foundry/Azure Machine Learning, AWS SageMaker and related AWS AI services, or Google Vertex AI.\n, • Knowledge of SQL, NoSQL, vector databases, graph databases, knowledge graphs, and data/platform technologies such as Kafka, Spark, and Airflow.\n, • Experience with cloud-native engineering and MLOps/LLMOps, including Docker, Kubernetes, Terraform, CI/CD, GitOps, MLflow or equivalent lifecycle and observability platforms.\n, • Strong understanding of REST/GraphQL APIs, microservices, event-driven architectures, distributed systems, enterprise integration patterns, and architecture for security, privacy, resiliency, scalability, performance, observability, and cost optimization.\n, • Experience with Spec-Driven Engineering, including requirements decomposition, architecture and API specifications, executable acceptance criteria, specification-to-code/test traceability, version control, and AI-assisted engineering workflows.\n, • Strong client-facing solutioning, stakeholder management, technical leadership, architecture documentation, and communication skills, with experience designing AI solutions for regulated industries.\n, • Knowledge of knowledge graphs, ontologies and Graph-RAG architectures\n\n \n Key Responsibilities \n\n • Architect end-to-end enterprise AI solutions spanning data ingestion, model/LLM integration, retrieval, orchestration, application integration, deployment, evaluation, monitoring, and governance.\n, • Design Generative AI, RAG, and Agentic AI solutions.\n, • Define Agentic AI architectures incorporating agent orchestration, tool/API integration, context and memory management, human-in-the-loop controls, guardrails, evaluation, and observability.\n, • Evaluate and select appropriate LLMs, SLMs, embedding models, AI frameworks, retrieval approaches, and deployment patterns based on accuracy, latency, security, scalability, and cost.\n, • Architect AI solutions using services across AWS, Microsoft Azure, and Google Cloud, with deep expertise in at least one hyperscaler.\n, • Design cloud-native and distributed architectures using APIs, microservices, event-driven patterns, containers, and Kubernetes.\n, • Define enterprise AI security and governance controls covering identity and access, data privacy, responsible AI, model security, auditability, and regulatory requirements.\n, • Lead solution discovery, architecture definition, technical assessments, POCs, reference architectures, reusable accelerators, and productionization.\n, • Drive Spec-Driven Engineering across the AI solution lifecycle by translating business intent, architecture decisions, functional and non-functional requirements, interfaces, guardrails, and acceptance criteria into version-controlled, machine-consumable specifications that guide design, code generation, testing, validation, and deployment.\n, • Partner with business stakeholders, enterprise architects, product teams, data scientists, AI engineers, DevOps/platform teams, and security teams.\n, • Provide technical leadership, conduct architecture/design reviews, mentor engineering teams, and communicate solution trade-offs to technical and executive stakeholders.\n\n

Through our Residential and Commercial business units, Vector Security delivers smart security, life safety, video, access control, and monitoring solutions. Vector Security Networks (VSN). Vector Security is a Drug-Free Workplace.

About the Role The Applied AI Engineer turns research and off-the-shelf models into systems the business actually runs on, pricing, risk, research workflows, or internal tooling. If a model ships but never gets integrated into a real workflow, it doesn't matter how good it is; this role is the difference between a promising prototype and something a portfolio manager touches every day. What You'll Do • Design, build, and ship production AI features end to end, from model selection through integration and monitoring, • Fine-tune and evaluate LLMs and other models against real business tasks, not generic benchmarks, • Build the evaluation harnesses and guardrails needed to trust a model's output in a production setting, • Work directly with researchers, PMs, and engineers to translate a vague idea into a shipped tool, • Own the full lifecycle of what you build: performance, cost, reliability, and iteration Must-haves • 3+ years shipping production software, with hands-on experience building applied AI or ML-backed features, not just research notebooks. This is non-negotiable for the role, • Strong Python and solid engineering fundamentals: testing, version control, code review, • Practical experience with LLM APIs, fine-tuning, or retrieval-augmented systems, • Comfortable owning a project from ambiguous spec to production Nice-to-haves • Experience in a regulated or high-stakes environment (finance, healthcare) where correctness and auditability matter, • Familiarity with vector databases, embeddings, or agentic workflows, • Prior exposure to a quant or trading environment, • Open-source contributions or public writing on applied AI work Why This Role This is a seat where the work ships fast and gets used immediately, not a research role that ends at a slide deck. The team is small enough that one engineer's judgment on what to build, and what not to, actually shapes the roadmap.

Snowflake AI Engineer – Cortex Location: New York City - Hybrid 2 days per week Contract Length: 6 Months Initial Rate: $100-$120 hr About the Role: We’re seeking a skilled Snowflake AI Engineer to help build AI-powered solutions on the Snowflake platform. In this role, you’ll develop applications using Snowflake Cortex, design semantic models, and build the data and AI foundations that let users get answers from their data. Your work will directly shape how the organization puts AI into production on Snowflake. Key Responsibilities: Snowflake Cortex Development • Build AI solutions using Snowflake Cortex, including Cortex Analyst, Cortex Search, Cortex Agents, and AI Functions. Turn business use cases into reliable, production-ready AI applications. Semantic Modeling • Design and maintain semantic models and Semantic Views that allow business users to query data in natural language. Make sure models are accurate, well-defined, and aligned with business logic. RAG & Retrieval Solutions • Develop retrieval-augmented generation (RAG) pipelines using Cortex Search and vector embeddings. Optimize chunking, retrieval, and prompt design to improve answer accuracy. AI Agents & Integrations • Build AI agents and integrations that connect Snowflake to other systems and tools, including APIs and MCP-based tooling. Evaluation & Quality • Set up testing and evaluation frameworks to measure AI output accuracy, cost, and performance. Put guardrails in place so outputs are trustworthy and traceable to source data. Data Foundations • Build and maintain the data pipelines and dbt models that power AI use cases, making sure data is clean, structured, and ready for AI applications. Collaboration & Support • Work closely with data engineers, analysts, and business stakeholders to understand requirements and deliver AI solutions that solve real problems. Required Skills & Experience: • Strong hands-on experience with Snowflake, including SQL and cloud data architecture, • Experience building with Snowflake Cortex or other LLM/AI tools, • Understanding of RAG, embeddings, and prompt engineering, • Python development experience for AI and data workflows, • Hands-on experience with dbt, • Proficiency with Git/GitHub for version control, • Self-starter who can work independently while collaborating effectively with cross-functional teams Nice to Have: • Experience with Cortex Agents, Semantic Views, or Streamlit in Snowflake, • Experience building AI agents or MCP tooling, • Snowflake certifications, such as SnowPro Core or Advanced

Founding AI Lead, Forward Deployed Engineering About the Opportunity A leading global alternative asset management firm, with more than $300 billion in assets under management and teams across private equity, impact, credit, real estate, and market solutions, is hiring a founding AI lead to help build a new Forward Deployed Engineering (FDE) team. This is a builder-leader role. You'll set up the function from scratch: hiring the team, defining how it operates, and setting the technical bar. You'll also stay hands-on, writing code and shipping production-ready AI products inside the firm's highest-value workflows. You'll start with a small team of VP-level engineers and scale the capability as demand and impact grow. You'll work directly with Partners, Managing Directors, and department heads to find the problems worth solving, shape ambiguous opportunities into real plans, and decide when a prototype is ready to become a product. What You'll Do • Build and lead the FDE function, starting with VP-level engineers. Hire, mentor, and retain strong engineers, and set the culture, standards, and talent model as the team grows., • Manage team capacity, prioritization, and resource allocation to maximize business impact across the FDE portfolio., • Define the operating model: how opportunities are identified, prioritized, scoped, evaluated, shipped, adopted, handed off, scaled, or retired., • Build AI products, digital coworkers, and workflow solutions that solve meaningful business problems across the firm., • Guide the team on when to use agentic workflows, multi-agent architectures, retrieval systems, automation, traditional software, process redesign, or simply recommend not building at all., • Set technical standards for AI products, including architecture patterns, security, access controls, observability, documentation, support expectations, and production readiness., • Establish firm-wide standards for AI evaluation, reliability, and release readiness, covering quality, safety, business effectiveness, regression testing, and model or workflow drift., • Partner with Security, Compliance, Legal, Data, Infrastructure, and application teams so AI solutions respect information barriers, entitlement models, audit requirements, and secure development practices., • Partner with senior stakeholders to set clear expectations on what AI systems can and cannot do. What We're Looking For • 10+ years of experience in software engineering or AI engineering and experience leading teams and delivering complex enterprise solutions., • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field (equivalent practical experience considered)., • A proven record of building teams and setting technical standards, raising the bar without creating unnecessary bureaucracy., • Experience building, scaling, or transforming an engineering function, platform, or capability, including the standards, talent model, and operating cadence, • Hands-on AI application development, including model integration, context and retrieval design, evaluation frameworks, agentic workflows, workflow orchestration, human-in-the-loop processes, and production deployment., • Experience building AI solutions on unstructured data such as investment memos, CIMs, credit agreements, LP communications, contracts, financial statements, and presentations., • Strong production engineering discipline: code review, testing, version control, CI/CD, secure development, documentation, and operational ownership., • A product mindset: you identify the underlying problem, weigh alternative approaches, and deliver solutions people actually adopt., • The ability to earn trust quickly with senior stakeholders, communicate trade-offs clearly, and turn ambiguous business needs into an executable technical plan., • Financial services fluency, with interest in or experience with investment, fund operations, or financial services workflows. Technology The team is technology agnostic and picks the right tool for each problem. You'll need credibility in modern AI application development and enterprise-grade software delivery. The team works with a range of technologies, including: • Python, TypeScript, JavaScript, Java, .NET, or similar languages, • OpenAI, Anthropic, Gemini, Azure AI, Microsoft Copilot, and Copilot Studio, • Agentic and multi-agent architectures, tool calling, orchestration frameworks, and RAG, • Evaluation, observability, and model monitoring frameworks, • APIs, integrations, workflow automation, and distributed systems, • Azure, AWS, Google Cloud, and cloud-native architectures, • Databricks, SQL Server, vector databases, and modern data platforms, • CI/CD, test automation, and secure development practices Why Join? • Founding role: You'll build the function, its standards, and its culture from the ground up, with real input on how AI gets built and deployed across the firm., • High-value problems: Your work will sit inside core investment and fund workflows, with direct exposure to senior investment professionals and operating leaders., • Ownership: You decide what gets built, what gets bought, and what gets left alone, and you own the path from prototype to production., • Real constraints, real impact: Information barriers, entitlements, and audit requirements are part of the job, so what you ship has to work in a regulated environment and get used., • Scale potential: You'll start with a small team of senior engineers and have the chance to grow the function as demand and impact increase., • Broad technical latitude: The team is technology agnostic, so you'll work across multiple model providers, cloud platforms, and modern data tooling.

The New York City Department of Health and Mental Hygiene's Division of Environmental Health works to prevent and control illness and injury related to environmental and occupational health risks through outreach, education, surveillance and enforcement. With staff of 1,000, the Division covers a broad range of subject matter, including oversight of environmental investigations, lead poisoning, injury prevention, occupational health, food safety, child care, radiation control, recreational and drinking water quality, air quality, climate health, vector control, veterinary public health and pest control. The Division of Environmental Health seeks an Exterminator L-I for its Bureau of Veterinary and Pest Control Services. Duties will include but not be limited to: inspecting premises and investigating complaints of infestation and determine the appropriate method of extermination to be used. Properly bait areas according to protocol; strictly applied appropriate dosage of rodenticide according to the labels and post signs and alerts where pesticides have been applied in public areas; maintain a extermination schedule of bait application in accordance to protocol and label directions; keep records via a computer of exterminating operations and make reports thereon. Instruct the public on safety and precautions before and after application of pesticides; inspect demolition worksites to confirm that adequate pre-demolition rodent control procedures have been performed; properly use and maintain all appropriate and applicable city-issued equipment, materials and clothing. Attend all required trainings and meetings; operates city vehicle safely and in accordance to the laws of the State. Preferred skills: Candidate should be highly organized, with the ability to work well in teams, should possess excellent verbal, written, and interpersonal skills. Experience working with computer would be a plus. Why you should work for us: • Loan Forgiveness: As a prospective employee of the City of New York, you may be eligible for federal/state loan forgiveness and repayment assistance programs that lessen your payments or even fully forgive your full balance., • Benefits: City employees are entitled to unmatched benefits such as: a premium-free health insurance plan that saves employees over $10K annually, per a 2024 assessment. Additional health, fitness, and financial benefits may be available based on the position's associated union/benefit fund. A public sector defined benefit pension plan with steady monthly payments in retirement. A tax-deferred savings program and a robust Worksite Wellness Program that offers resources and opportunities to keep you healthy while serving New Yorkers., • Work From Home Policy: Depending on your position, you may be able to work up to two days during the week from home., • Job Security - you could enjoy more job security compared to private sector employment and be able to contribute to making NYC a healthy place to live and work. Established in 1805, the New York City Department of Health and Mental Hygiene (NYC Health Department) is the oldest and largest health department in the U.S., dedicated to protecting and improving the health of NYC. Our mission is to safeguard the health of every resident and cultivate a city where everyone, regardless of age, background, or location, can achieve their optimal health. We provide a wide array of programs and services focused on food and nutrition, anti-tobacco support, chronic disease prevention, HIV/AIDS treatment, family and child health, environmental health, mental health, and social justice initiatives. As the primary population health strategist and policy authority for NYC, with a rich history of public health initiatives and scientific advancements, from addressing the 1822 yellow fever outbreak to the COVID-19 pandemic, we serve as a global leader in public health innovation and expertise. Come join us and help to continue our efforts in making a difference in the lives of all New Yorkers! The NYC Health Department is an inclusive equal opportunity employer committed to providing access and reasonable accommodation to all individuals. To request reasonable accommodation to participate in the job application or interview process, contact Sye-Eun Ahn, Director of the Office of Equal Employment Opportunity, at sahn1@health.nyc.gov or 347-396-6549. Job ID: 783846

Take2 has proven experience bridging the intersection of technology and people solutions. As a proven, trusted provider for our Federal and commercial clients, we provide the right solutions, at the right time through trusted partnerships, customized to solve our client’s unique business challenges. Take2 invests time, discipline, and rigor into our technology and people solutions, as well as utilizes our proprietary People Cloud. Whether we are bridging the gap between IT talent and our customers’ business challenges, Take2 will work as a partner to best resolve client needs. Take2 is hiring a Database Developer who is eligible to be sponsored for a Public Trust Clearance. This position is Remote, but it will require you to work East Coast Hours while being located in the United States. Database Developer What You Will Do We are seeking a highly motivated Developer DBA with strong Oracle SQL and PL/SQL expertise, ETL development experience, and cloud data platform knowledge to support application modernization, database development, systems integration, analytics, and operational support activities. • Design, develop, and support Oracle database solutions, including packages, stored procedures, functions, triggers, views, materialized views, and sequences, ensuring high performance, scalability, and maintainability., • Develop, enhance, and optimize SQL and PL/SQL code to support application functionality, reporting, system integrations, and business operations., • Create and maintain database migration scripts, schema updates, release deployment packages, and automated database deployment processes., • Design, build, and support ETL workflows, data transformation processes, validation frameworks, and batch data processing solutions., • Analyze and interpret complex data models, database schemas, enterprise data flows, ERDs, and data mappings to support business and application requirements., • Develop and support cloud-based data integration, reporting, and analytics solutions using AWS technologies such as Amazon Redshift, Amazon S3, Amazon RDS, and related services., • Build and maintain data integration pipelines using Matillion ETL and other enterprise data integration platforms., • Troubleshoot and resolve database issues, data quality concerns, application integration challenges, and performance bottlenecks across environments., • Perform database performance tuning and optimization using execution plans, indexing strategies, partitioning, optimizer statistics, and Oracle diagnostic and monitoring tools., • Collaborate closely with software engineers, architects, DevOps engineers, and business stakeholders to deliver scalable and reliable data solutions., • Participate in Agile development activities, including sprint planning, backlog refinement, daily standups, code reviews, sprint reviews, and retrospectives., • Contribute to DevSecOps and CI/CD initiatives by implementing automated testing, deployment, monitoring, and compliance practices for database solutions., • Create and maintain technical documentation, including database designs, data mappings, interface specifications, operational procedures, and support guides., • Develop and support database unit testing, regression testing, data validation testing, and automated test support for SQL, PL/SQL, ETL, and data migration changes., • Support production operations, release deployments, incident troubleshooting, root-cause analysis, and post-deployment validation for mission-critical database and application components., • Leverage approved AI-powered development tools to accelerate SQL and PL/SQL development, code review, troubleshooting, documentation, testing, and knowledge-sharing activities., • Identify and implement opportunities to apply AI and intelligent automation to database development, data engineering, deployment, monitoring, operational support, and engineering productivity., • Support data governance, security, privacy, and compliance requirements by implementing least-privilege access, auditability, encryption-aware data handling, and controls aligned with Federal standards such as FISMA, NIST, and FedRAMP where applicable., • Continuously evaluate emerging database, cloud, AI, and data engineering technologies and recommend improvements that enhance platform capabilities and team productivity. What You Will Need • Bachelor’s degree required., • Minimum of five (5) years of experience in Oracle database development, database engineering, ETL development, data integration, or related software engineering roles., • Strong experience in Oracle SQL and PL/SQL development, including packages, procedures, functions, triggers, views, materialized views, sequences, complex queries, performance tuning, and Oracle development tools such as SQL Developer and SQL*Loader., • Proven ability to design, develop, optimize, troubleshoot, and maintain database solutions supporting enterprise and mission-critical applications., • Experience designing and implementing ETL solutions, data transformation processes, batch processing frameworks, and data migration initiatives., • Experience with AWS data and cloud services, including Amazon Redshift, Amazon RDS, Amazon S3, and related analytics and integration technologies., • Experience with Matillion ETL or similar cloud-native data integration, orchestration, and data pipeline platforms., • Strong understanding of relational database architecture, logical and physical data modeling, ERDs, normalization, indexing, query optimization, transaction management, and referential integrity., • Experience analyzing and supporting complex enterprise application databases, schemas, and data models., • Experience developing or supporting database unit tests, regression tests, data validation checks, and deployment verification activities., • Experience supporting production releases, operational incidents, defect triage, root-cause analysis, and post-release validation in enterprise or mission-critical environments., • Ability to troubleshoot and resolve database, data quality, integration, and application performance issues across distributed environments., • Experience supporting database and application deployments using CI/CD pipelines, release automation, and DevSecOps best practices., • Experience working in Agile software development environments utilizing Scrum, Kanban, or similar methodologies., • Experience using source control and application lifecycle management tools such as Git, GitHub, Bitbucket, GitLab, or Azure DevOps., • Experience using approved AI-assisted tools or automation practices to support code generation, optimization, testing, troubleshooting, documentation, code reviews, knowledge management, and engineering productivity improvements., • Understanding of Responsible AI principles, AI governance, cybersecurity, data privacy, and secure AI adoption within enterprise or government environments., • Familiarity with AI-enhanced SDLC practices, AI-assisted DevSecOps, intelligent automation, and emerging AI engineering patterns., • Strong analytical, problem-solving, communication, and organizational skills, with the ability to manage competing priorities, work independently or collaboratively, and continuously adapt to emerging database, cloud, and AI technologies. What Would Be Nice To Have • Experience supporting Federal Government or large-scale enterprise applications., • Experience supporting Grants Management, Financial Management, Case Management, Regulatory, or workflow-driven systems., • Experience with Oracle Data Pump, Oracle GoldenGate, Informatica, Talend, ODI, Liquibase, Flyway, or similar data integration and migration tools., • Experience with PostgreSQL, SQL Server, MySQL, or other enterprise database platforms., • Experience supporting cloud modernization, database migration, or application modernization initiatives., • Knowledge of Federal data security and compliance practices, including audit logging, least-privilege access, encryption-aware data handling, and security controls aligned with FISMA, NIST, or FedRAMP requirements., • Experience with data warehousing concepts, dimensional modeling, enterprise reporting, and business intelligence platforms such as Power BI, Tableau, or Amazon QuickSight., • Experience supporting data pipelines and data platforms used for analytics, reporting, AI, and machine learning workloads., • Familiarity with AWS cloud-native application and service deployment architectures., • Oracle certifications preferred, including:, • Oracle Certified Professional (OCP), • Oracle Database Administrator Certified Professional, • Oracle SQL Certified Associate, • Experience evaluating and adopting emerging AI technologies to improve software engineering productivity, database development, operational efficiency, and modernization initiatives., • Familiarity with modern AI data architectures, vector databases, retrieval-augmented generation (RAG), AI agents, knowledge management systems, and enterprise AI platforms., • Experience participating in AI-driven modernization efforts, intelligent automation initiatives, or enterprise data and analytics programs., • Hands-on experience with AI-powered development tools such as GitHub Copilot, Microsoft Copilot, Amazon Q Developer, Cursor, ChatGPT Enterprise, Claude, Gemini, or similar platforms.

The Bureau of Communicable Disease (BCD), part of the Division of Disease Control, is responsible for the surveillance, prevention, and control of over 70 infectious diseases including foodborne, enteric, waterborne, respiratory (including COVID-19), zoonotic and vector borne diseases. Within BCD, t