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Overview We're seeking talented Performance Engineers with deep expertise in low-level systems optimization — specifically C++, Python, and Rust — to bring hands-on technical excellence and elevate the quality of our AI training and inference infrastructure data. Key Responsibilities - Guide res

Job DescriptionAkamai Expert Engineer (Green Card/USC) Core skills Manage confirmation for Akamai Automation of configuration mgt in Akamai tool Very hands on with Akamai CDN Responsibilities: Design, develop, and implement automation solutions for Akamai configurations. Create and maintain scripts and tools to automate the deployment and management of Akamai services. Collaborate with development, operations, and security teams to integrate automated Akamai solutions into the overall infrastructure. Monitor and analyze the performance of automated configurations to ensure optimal operation. Troubleshoot and resolve issues related to automated Akamai configurations. Qualifications: Extensive experience with Akamai technologies, including CDN, WAF, and other performance and security solutions. Strong proficiency in scripting languages such as Python, Perl, or Shell. Experience with automation tools and frameworks (e.g., Ansible, Terraform, Jenkins). Strong communication and collaboration skills.

Job DescriptionSenior AI Engineer – Google AI & Generative Intelligence Job Title: Senior AI Engineer – Google AI & Generative Intelligence Location: Paramus, New Jersey (Hybrid) Duration: 6 Months Employment Type: Contract-to-Hire Position Overview We are seeking a highly experienced Senior AI Engineer with strong expertise in Google AI technologies, Generative AI, and cloud-native AI application development. The ideal candidate will bring 10–15 years of software engineering experience, including 5+ years focused on Artificial Generative Intelligence, building scalable AI systems, LLM/SLM applications, RAG architectures, and multi-agent solutions in production environments. This role requires deep hands-on experience with the Google AI ecosystem including Gemini, Vertex AI, Google Agent Development Kit (ADK), Google AI Studio, and Google Workspace integrations. Key ResponsibilitiesLarge & Small Language Model Engineering • Design, develop, and deploy AI agents leveraging commercial LLMs including:, • Gemini (Google), • GPT (OpenAI), • Claude Sonnet (Anthropic), • Work with open-source and self-hosted LLMs such as:, • Mixtral (Mistral AI), • Build lightweight SLM-based solutions using:, • Phi-3, • Gemma, • Mistral, • Fine-tune and customize models using:, • Vertex AI Tuning, • Hugging Face Transformers, • PEFT methods including LoRA and QLoRA, • Utilize frameworks such as:, • PyTorch, • TensorFlow, • JAX, • Perform synthetic data generation and model evaluations using:, • HELM, • lm-evaluation-harness, • Custom benchmarking frameworksGoogle AI & Workspace Integration, • Design AI-powered workflows integrated with:, • Google Workspace, • Google Docs, • Sheets, • Drive, • Gmail, • Meet, • BigQuery, • Lakehouse platforms, • Develop intelligent AI agents using Google Agent Development Kit (ADK), • Utilize:, • Google AI Studio, • VS Code, • Work extensively with Google Cloud Platform (GCP) services:, • Vertex AI, • GKE (Google Kubernetes Engine), • Cloud Run, • Cloud Functions, • Vertex AI Vector DatabasesAI Solution Design & Planning, • Lead requirements gathering and technical documentation using Confluence, • Create AI workflows and system architecture diagrams using Lucidchart, • Design UI/UX prototypes using Figma, • Manage Agile sprint planning and delivery using Jira, • Prepare, clean, and organize enterprise datasets for AI/ML workflows, • Conduct data analysis using Jupyter Notebooks and pandas, • Utilize Hugging Face Model Hub for model research and selectionDevelopment Frameworks & AI Tooling, • Build orchestration pipelines using:, • LangChain, • LlamaIndex, • LangGraph, • Develop multi-agent AI systems using:, • Semantic Kernel, • LangGraph, • Manage prompt engineering and observability using:, • LangSmith, • PromptLayer, • Deploy models locally using Ollama and at scale using vLLM, • Track experiments using:, • MLflow, • Weights & Biases, • Manage source control with GitVector Databases & RAG Architecture, • Build Retrieval-Augmented Generation (RAG) systems using:, • Vertex AI Vector DB, • ChromaDB, • Design enterprise semantic search and knowledge retrieval architecturesBackend Development, • Develop scalable RESTful APIs using:, • FastAPI (Python), • Express.js (Node.js), • Manage APIs using:, • MuleSoft, • ApigeeFrontend Development, • Develop modern AI-driven user interfaces using:, • React, • Angular, • Material-UI, • Collaborate on UI/UX workflows and prototyping using FigmaTesting, Quality & Observability, • Perform LLM and RAG evaluations using:, • RAGAS, • DeepEval, • LangSmith Evaluators, • Create unit tests using pytest, • Monitor model performance and hallucination detection, • Track AI infrastructure costs using:, • OpenMeter, • Custom dashboardsDeployment & Infrastructure, • Deploy AI systems using:, • Kubernetes, • Google GKE, • Build CI/CD pipelines using:, • GitHub Actions, • GitLab CI, • Support:, • Cloud deployments, • Hybrid deployments, • Edge AI inference environmentsRequired Qualifications, • 10–15 years of overall software engineering experience, • 5+ years of hands-on Generative AI experience, • Strong expertise with:, • Gemini, • Vertex AI, • Google ADK, • Google AI Studio, • Google Workspace integrations, • Strong Python development experience, • Familiarity with Node.js, • Experience with:, • RAG systems, • Multi-agent AI architectures, • LLM/SLM fine-tuning, • LoRA / QLoRA / PEFT, • AI evaluation frameworks, • Strong cloud-native development experience on GCP, • Experience with MLOps and AI CI/CD pipelinesPreferred Qualifications, • Google Cloud certifications such as:, • Professional ML Engineer, • Professional Cloud Architect, • Experience contributing to open-source AI/ML projects, • Experience with edge AI and hybrid cloud deployments, • Experience building synthetic data generation pipelines, • Prior mentoring or leadership experience within AI/ML teams For more details reach at resumes@navitassols.com

Job DescriptionSr. Azure DevSecOps Engg. Location - NJ Need 2-3 days onsite ( Hybrid ) . Need candidates only with 12 + years experience . No H1B Transfer Candidates OR OPT/CPT This is a DevSecOps Role and not DevOps. Strong Azure Services, SAST/DAST , GitHub, Kubernetes, AKS , Terraform and Python Scripting experience is required. Our client is seeking a highly skilled DevSecOps Engineer to design, build, and maintain secure and scalable CI/CD pipelines for application and database deployments. Key Responsibilities: Design and maintain CI/CD pipelines for applications and databases using tools such as Azure DevOps, Jenkins, Smart City, GitLab CI, or GitHub Actions. Automate infrastructure provisioning and configuration management using tools like Terraform, Ansible, or Helm. Integrate automated testing frameworks (junit, Slenium etc) and code coverage tools (e.g., SonarQube etc). Embed static and dynamic security scanning tools (SAST/DAST) into pipelines. Implement and monitor database CI/CD workflows for version-controlled schema migrations. Ensure secure secrets management using Azure Key Vault. Continuously monitor pipeline performance and enforce compliance, code quality, and security policies. Collaborate with application and database developers to optimize release strategies and rollback mechanisms. Conduct incident response drills, threat modeling, and vulnerability assessments within CI/CD contexts. Document DevSecOps processes and provide training to development teams on security and best practices. Required Skills & Experience: Proven experience with DevSecOps practices and tools. Proficiency in CI/CD platforms like Azure DevOps, Smart City, GitHub Actions, GitLab CI, or Jenkins. Solid understanding of cloud platforms (Azure, ). Experience with IaC tools like Terraform, CloudFormation. Strong background in code testing frameworks and code quality tooling (JUnit, SonarQube, etc.). Hands-on with database CI/CD, schema versioning, and database migration practices. Experience with containerization (Docker) and orchestration (Kubernetes, AKS). Familiarity with secure coding principles and compliance standards. Strong scripting skills in Python, Bash. Preferred Qualifications: Certifications: Azure DevOps Engineer. Experience with monitoring and observability tools. Experience in multi-cloud or hybrid-cloud DevSecOps pipelines. Familiarity with data masking, auditing, and encryption in the database CI/CD context. Flexible work from home options available.

Job DescriptionCompany Description VERSANT is a leading force in news, sports and entertainment - home to iconic and trusted brands that inspire, inform, and delight audiences. Our unique combination of content, technology and services enriches the cultural fabric, igniting passions, sparking conversations, and connecting people to what they love most. As an independent, publicly traded company, VERSANT brings together powerhouse cable networks - including USA Network, CNBC, MS NOW (formerly MSNBC), Oxygen, E!, SYFY, and Golf Channel - with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. Together, these businesses reflect our commitment to delivering exceptional experiences across every screen and service. VERSANT is an industry-changing media company fueled by innovation and an entrepreneurial spirit. With a strong foundation and a forward-looking vision, VERSANT empowers creativity, embraces change, and drives connection in an ever-evolving world. Job Description ABOUT THE ROLE Fandango is looking for a SENIOR PLATFORM ENGINEER to build our next big thing in platform growth across Fandango, Rotten Tomatoes, Fandango at Home. In this role, you'll join the Platform Operations team and report to the Sr. Director of Platform Operations, contributing to the foundational infrastructure and tools that power how we enable developer productivity while delivering platform enhancements. As a Platform Engineer, you will focus on building and maintaining the core platform layers that support our engineering organization. If you enjoy solving complex problems, building for scale, and making a measurable impact – we'd love to meet you. WHAT YOU'LL DO As a Senior Platform Engineer on our team, you will: • Build and maintain core platform infrastructure that serves as the foundation for engineering teams across the organization, • Drive and participate in solution architecture and delivery across diverse domains, offering expertise in AWS cloud infrastructure and resources, containers (ECS/Kubernetes) and cloud-native architectures, • Develop, enhance, and operate platform capabilities including CI/CD pipelines, infrastructure as code, reusable patterns, and automation solutions that enable rapid, reliable, and secure deployments, • Design and implement standardized, reusable cloud infrastructure patterns and templates that help teams adopt best practices while maintaining security and compliance requirements, • Demonstrate, enable, and promote consistent adoption of software delivery practices and solutions that optimize for fast feedback, observability, and operational excellence, • Proactively collaborate with product and engineering teams, taking technical leadership in areas of cross-functional projects while sharing knowledge and best practices, • Evaluate existing standards and practices, identify gaps, and implement improvements to strengthen Development, Security, and Operational practices across the organization, • Demonstrate excellent communication skills through proactive status updates, clear documentation, knowledge sharing, and effective collaboration when facing technical challenges, • Partner closely with engineering teams to understand their needs, refine requirements, and deliver solutions that enhance developer productivity while meeting project objectives, • Work with emerging technologies around AI, MCP, and RAG, • Cost optimization - Monitor and optimize cloud spend, implementing cost governance strategies and right-sizing recommendations., • Service reliability Maintain SLOs/SLIs/SLAs, improve uptime targets, and help implement reliability engineering practices., • Mentorship - Mentor junior and mid-level engineers, conduct design reviews, and raise the technical bar across the platform team.Qualifications WHAT WE'RE LOOKING FOR: • AWS Expertise: 6+ years of hands-on experience with AWS, with a focus on Infrastructure as Code, • Linux Proficiency: Minimum of 4 years of experience managing and maintaining Linux systems, • Automation/Scripting: 3+ years of experience with Python for automation and scripting, • Git and GitOps: Practical experience and comfortable using Git and automated workflows, • AWS Security Knowledge: Familiarity with AWS security best practices, including DNS, secure VPCs, and database security (e.g., PostgreSQL, MySQL), • Communication & Collaboration: Strong written and verbal communication skills with the ability to explain complex technical concepts to technical and non-technical audiences, • Problem-Solving Mindset: Eagerness to learn, grow, and tackle challenges in a fast-paced environment, • Troubleshooting & debugging - Proven ability to troubleshoot complex distributed systems issues across networking, compute, storage, and application layers. Comfortable with packet captures, log analysis, performance profiling, and diagnosing intermittent failures in production.\, • Terraform / Infrastructure as Code: 3+ years of hands-on experience with Terraform, including module development, state management, and multi-environment workflows. Comfortable writing, reviewing, and maintaining IaC that provisions and manages cloud infrastructure at scale., • Networking fundamentals — VPCs, load balancers, DNS, CDNs, service mesh, network troubleshooting., • Monitoring/Observability — Datadog, Prometheus, Grafana, CloudWatch, ELK stacks., • Incident management experience — PagerDuty, on-call rotations, post-mortem culture. BONUS POINTS FOR: • AWS Certifications: Relevant certifications such as AWS Certified Cloud Practitioner, AWS Certified Solutions Architect – Associate, • Background in building or maintaining systems that support scalable application environments and event-driven architectures, • Understanding of container security and orchestration (Docker, Kubernetes), • Fundamentals of running AI-related services, • Experience contributing to open-source projects or internal platform tools, • Multi-account AWS strategy (Organizations, Control Tower, Landing Zones, • Chaos engineering / game days, • Platform-as-a-product thinking (internal developer portals, Backstage) Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. For LA County and City Residents Only: VERSANT Media will consider for employment qualified applicants with criminal histories, or arrest or conviction records, in a manner consistent with relevant legal requirements, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, where applicable. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to candidateaccessibility@versantmedia.com. VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc. VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.

Job Description Senior Data Engineer – Cloud & AI Platforms Location: US / Canada (Remote/Hybrid) Type: Contract / Full-Time Overview: We are hiring a Senior Data Engineer to support large-scale data modernization and AI-driven transformation programs. This role focuses on building robust, scalable cloud data platforms and enabling advanced analytics and AI use cases. Key Responsibilities: • Architect and develop scalable data pipelines and cloud-native data solutions, • Collaborate with data scientists, analysts, and business stakeholders, • Ensure high performance, data quality, and governance across platforms Required Skills: • Strong experience in data engineering and cloud-based architectures, • Hands-on expertise with platforms like Databricks, Snowflake, Azure Synapse, or BigQuery, • Proficiency in AWS, Azure, or GCP environments Nice to Have: • Experience with ML/AI pipelines (Python, PyTorch, MLOps), • Exposure to GenAI frameworks such as LangChain or agent-based systems, • Familiarity with AI governance and compliance standards For more details reach at resumes@navitassols.com.

Job DescriptionCompany Description On-Site 1yr contract $10950/month About the Role We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure. You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. Job Description • Design and develop algorithms for generative models using deep learning techniques, • Design and build LLM-powered applications for internal and/or customer-facing use cases, • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems, • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration, • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate, • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability, • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies, • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices, • Build monitoring, observability, and feedback loops for model and application performance in production, • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems, • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities, • Mentor other engineers and contribute to architecture, technical direction, and engineering best practices Qualifications • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience, • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production, • Strong programming skills in Python and experience with backend/API development, • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design, • Experience in optimizing RAG pipelines using both structured and unstructured data, • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent, • Experience in generative AI techniques such as GANs, and VAEs, • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search, • Experience with cloud platforms such as AWS, GCP, or Azure, • Experience with Docker, Kubernetes, CI/CD, and production deployment practices, • Strong understanding of software architecture, scalability, reliability, and distributed systems, • Experience building evaluation, testing, and monitoring for AI systems, • Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications • Experience fine-tuning or adapting open-source LLMs, • Advanced knowledge of natural language processing for text generation tasks, • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks, • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar, • Experience building multi-agent systems or advanced orchestration workflows, • Experience with AI safety, guardrails, red-teaming, privacy, and governance, • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems, • Experience in customer-facing or enterprise SaaS products, • Experience in semiconductor/manufacturing, retail and e-commerce sectors Additional Information All your information will be kept confidential according to EEO guidelines.

Job DescriptionBenefits: • 401(k) Software Engineer (Java/Full-Stack) Location: Fort Lee, NJ (Hybrid - 3 days/week in-office) Interview Mode: In person Interview Core Responsibilities • Create, develop, and sustain high-performance applications utilizing Core Java, Spring, and Spring Boot., • Construct and deploy scalable services within AWS environments while implementing effective data queries through GraphQL., • Employ JOLT for JSON-to-JSON transformations and XSLT for XML processing to guarantee smooth data integration across various systems., • Leverage Python for automation, scripting, or additional service development as required., • Collaborate closely with cross-functional teams to convert business requirements into technical specifications. Technical Qualifications • Demonstrated expert-level proficiency in Core Java and the Spring Framework, including Spring Boot, Spring MVC, and Spring Security., • Established experience with GraphQL and Amazon Web Services (AWS)., • A robust understanding of data mapping and transformation tools, particularly JOLT and XSLT., • A strong command of Python for backend logic or automation tasks. Requirements • At least 12 years of professional experience in software development., • Outstanding verbal and written communication abilities; capable of articulating intricate technical concepts to stakeholders without a technical background.

Job Description Position Title: Sr AI Engineer Location: Paramus, NJ Duration: 06 Month Contract Status: Hybrid Employment Type: Contract role on W-2 through Above and Beyond Talent Acquisition, Inc. (A&B Talent) Pay Range: USD $135 an hour W2 Client Info / Who they are: Above and Beyond Talent Acquisition proudly represents our Client, a global leader in water, waste, and energy management. The client offers a full spectrum of water, waste, and energy management services, including water and wastewater treatment, commercial and hazardous waste collection and disposal, energy consulting, and resource recovery. The client helps commercial, industrial, healthcare, higher education, and municipality customers throughout North America. The client has approximately 10,000 employees working at over 350 locations across the continent. Requirements / Who we are looking for: • 10–15 years of overall software engineering experience., • 5+ years of hands-on experience in Artificial Generative Intelligence, including LLMs, SLMs, RAG, and multi-agent systems., • Deep expertise in Google AI ecosystem: Gemini, Vertex AI, Google ADK, Google AI Studio, and Google Workspace integrations., • Proficiency in Python (primary) and familiarity with Node.js., • Strong background in cloud-native development on GCP., • Demonstrated experience with model fine-tuning (LoRA, QLoRA, PEFT) and model evaluation frameworks., • Solid understanding of MLOps, CI/CD for AI systems, and production deployment best practices., • Experience with multi-agent AI architectures using Semantic Kernel, or LangGraph., • Preferred Qualifications, • Google Cloud Professional certifications ( Professional ML Engineer, Professional Cloud Architect), • Contributions to open-source AI/ML projects., • Experience with edge AI deployments and hybrid cloud-edge inference., • Familiarity with synthetic data generation pipelines., • Prior experience mentoring junior engineers or interns in AI/ML domains. Performance Objectives / What you'll be doing: 1. Large & Small Language Model Engineering • Design, develop, and deploy Agents leveraging commercial LLMs such as Gemini (Google), GPT (OpenAI), and Claude Sonnet (Anthropic) for high-performance, large-context, and multimodal tasks., • Work with open-source/self-hosted LLMs including Mixtral (Mistral AI)., • Architect and implement SLM-based solutions using lightweight models such as Phi-3 (Microsoft), Gemma (Google), and Mistral for resource-constrained environments., • Lead fine-tuning and customization of models using Vertex AI Tuning, Hugging Face Transformers, and parameter-efficient fine-tuning (PEFT) methods including LoRA and QLoRA., • Apply training frameworks such as PyTorch, TensorFlow, or JAX for model experimentation and development., • Generate synthetic data and evaluate models using HELM, lm-evaluation-harness, and custom benchmarks. 1. Google AI & Workspace Integration • Lead the design and implementation of AI-powered solutions deeply integrated with Google Workspace (Docs, Sheets, Drive, Gmail, Meet), Big Query and Lakehouse., • Architect and build intelligent agents and workflows using Google Agent Development Kit (ADK)., • Leverage Google AI Studio as the primary IDE, VSCode for AI application development and prototyping., • Utilize Google Cloud Platform (GCP) services including:, • Vertex AI for ML model training, tuning, and deployment, • GKE (Google Kubernetes Engine) for container orchestration, • Cloud Run for serverless deployment, • Cloud Functions for event-driven AI tasks, • Vertex AI Vector DBs for semantic search and retrieval 1. Design & Planning • Lead requirements gathering using Confluence for documentation and team collaboration., • Create detailed system architecture diagrams and AI workflows using Lucidchart., • Design UI/UX prototypes in Figma for AI-powered application interfaces., • Manage project delivery and sprint planning using Jira., • Oversee data preparation and management: cleaning, transforming, and organizing data for AI/ML workflows., • Conduct data analysis using Jupyter Notebooks and pandas for exploration and preprocessing., • Leverage Hugging Face Model Hub for model comparison, selection, and download. 1. Development Frameworks & Tools • Orchestrate LLM/SLM applications using LangChain, LlamaIndex, and LangGraph., • Build multi-agent systems with Semantic Kernel, and LangGraph., • Manage and optimize prompts using LangSmith and PromptLayer., • Deploy models locally with Ollama or at scale with vLLM for efficient inference., • Track experiments, metrics, and results with MLflow or Weights & Biases., • Manage code and data versioning with Git. 1. Vector Databases & Semantic Search • Implement semantic search and Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Vector DBs and ChromaDB., • Design and optimize end-to-end RAG architectures for enterprise-grade knowledge retrieval. 1. Backend Development • Develop robust RESTful APIs using FastAPI (Python) or Express.js (Node.js)., • Manage and secure APIs using Mulesoft, Apigee. 1. Frontend Development • Build modern user interfaces using React or Angular., • Utilize Material-UI for consistent, accessible, and modern UI components., • Prototype and plan UI/UX workflows using Figma. 1. Development Tools & Code Quality • Write and debug code in VS Code with Python and GitHub Copilot extensions., • Leverage GitHub Copilot for AI-assisted code suggestions and productivity., • Manage source code with GitHub or GitLab., • Enforce code quality and standards using SonarQube, ESLint, and Pylint. 1. Testing & Quality Assurance • Conduct LLM-specific testing using RAGAS and DeepEval for LLM/RAG pipeline evaluation., • Use LangSmith Evaluators for prompt testing and hallucination detection., • Write and execute unit tests using pytest., • Ensure output quality and reliability using LangChain Evaluators and custom metrics. 1. Deployment & Infrastructure • Orchestrate containers at scale with Kubernetes (K8s), and Google GKE., • Automate CI/CD pipelines using GitHub Actions or GitLab CI., • Support on-premise, cloud (GCP/Vertex AI), and hybrid infrastructure deployments including edge devices for local inference. 1. LLM Monitoring & Observability • Monitor LLM performance and usage with LangSmith and Weights & Biases., • Track and optimize AI infrastructure costs using OpenMeter and custom dashboards., • Set up continuous evaluation pipelines to ensure ongoing model quality and reliability., • Monitor application and model performance end-to-end with LangSmith observability tools. Perks of working with US / What We offer: • Competitive Salary., • Health, dental, and vision insurance., • Company 401K plan The salary, other compensation, and benefits information are accurate as of the date of this posting. The Company reserves the right to modify this information at any time, subject to applicable law. “Above and Beyond Talent is an equal opportunity employer and staffing firm.”

Job DescriptionCompany Description 1. About StockStory VERSANT is an independent, publicly traded company that brings together powerhouse brands such as CNBC, MS NOW (formerly MSNBC), USA Network, Oxygen, E!, SYFY, and Golf Channel along with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. StockStory, now part of CNBC under VERSANT, is building the next generation of AI-powered equity research for individual investors. This is a chance to build products that can shape how millions of consumers understand markets and make investing decisions. We offer the best parts of a startup environment - small team, high ownership, fast execution, and room to experiment - with the backing and stability of VERSANT, an independent publicly traded media company. As an AI engineer, you will work on both an existing AI product with real user impact and greenfield projects with significant room for exploration. The work spans cutting-edge LLMs / ML, large-scale data systems, financial reasoning, and research tooling, with opportunities to apply ideas from functional programming and graph-based systems where they create real advantage. You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design. For an ambitious AI engineer, it is an unusual opportunity to work with cutting-edge technology and advanced data systems while learning firsthand how sophisticated investors analyze businesses and markets. Job Description We're looking for a Staff ML Engineer to lead the design and delivery of large-scale, production AI systems that power core products. A genuine interest in investing, public markets, and fundamental business analysis is expected. This role is for someone who combines deep machine learning expertise with strong software engineering and architectural judgment, and who is excited to solve ambiguous, high-leverage problems that shape both product capabilities and technical direction. You will work across teams to ensure our AI systems are reliable, scalable, and aligned with long-term product and infrastructure goals. You will design and operate end-to-end ML systems spanning data pipelines, training workflows, inference services, evaluation, and monitoring, while helping define how AI is applied across the company. This role is especially well suited to engineers who want to pair hands-on technical depth with cross-functional influence and long-term platform thinking. This role sits within a small and growing, high-caliber team where individuals are expected to operate with a high degree of ownership and autonomy, contributing directly to core product, infrastructure, and modeling decisions while working closely with engineering and senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers. Qualifications 1. What We're Looking For: · Bachelor’s degree in Computer Science or equivalent practical experience · Minimum of 5 years of experience in software engineering with a focus on machine learning or AI systems · Experience building and operating production ML systems · Strong proficiency in Python, TypeScript, or Java · Proven experience with LLMs, ranking or recommendation systems, search, or applied NLP · Deep understanding of modern ML techniques, including deep learning and representation learning · Demonstrated ability to lead technical initiatives across teams · Ability to proactively share ML knowledge and best practices, fostering a collaborative and non-siloed engineering culture 1. What You'll Do: · Lead the architecture and implementation of production ML and AI systems used at scale · Drive technical strategy for AI across multiple product areas · Design end-to-end systems including data pipelines, training workflows, inference services, evaluation, and monitoring · Own and deliver high-impact projects with significant ambiguity · Provide technical leadership through design reviews, mentorship, and cross-team collaboration · Identify and mitigate systemic risks in AI systems, including performance regressions, bias, and operational failure modes · Guide model lifecycle management, monitoring, and evaluation practices 1. Requirements: · Bachelor’s degree in Computer Science or equivalent practical experience · Minimum of 5 years of experience in software engineering with a focus on machine learning or AI systems · Experience building and operating production ML systems · Strong proficiency in Python, TypeScript, or Java · Proven experience with LLMs, ranking or recommendation systems, search, or applied NLP · Deep understanding of modern ML techniques, including deep learning and representation learning · Demonstrated ability to lead technical initiatives across teams · Ability to proactively share ML knowledge and best practices, fostering a collaborative and non-siloed engineering culture Prior experience leading or founding an AI systems team · Hands-on experience with neural networks, including CNNs, RNNs, Transformers, or other deep learning architectures · Background in classical and modern NLP techniques such as tokenization, sequence labeling, language modeling, embeddings, text classification, and information extraction · Experience with large-scale training pipelines using frameworks such as TensorFlow or PyTorch · Experience building human-in-the-loop training or evaluation workflows 1. Location: At CNBC Headquarters in Englewood Cliffs, NJ, you’ll have access to great perks and amenities: • Sweat it out -- Free onsite fitness center with state-of-the-art equipment, plus daily group classes, • Eat up -- Gourmet cafeteria with daily specials plus soup and salad bars, • Extras -- Dry cleaning, shoe shining and sneak peeks, • Don’t have a car? No problem! We offer free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City In addition to these benefits, employees in this group will be joining at a time of meaningful and continued investment in data, technology, and product development, with the opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time, offering meaningful exposure to senior leadership and the ability to influence how the platform evolves. Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to candidateaccessibility@versantmedia.com. VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc. VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.

Job Description We are looking for a System Engineer with DevOps experience to join our team. The ideal candidate will have 2–3 years of experience in system administration, automation, cloud infrastructure, and deployment support, with hands-on experience in Kubernetes, Python, Helm, and Terraform. Key Responsibilities • Manage and support system infrastructure, servers, and environments., • Build and maintain CI/CD pipelines and deployment automation., • Work with Kubernetes to deploy and manage applications., • Develop automation scripts using Python., • Create and maintain Helm charts for application packaging and deployment., • Use Terraform to provision and manage infrastructure., • Troubleshoot system, application, and deployment issues., • Monitor performance, availability, and reliability of systems., • Collaborate with development, QA, and operations teams. Requirements Required Skills • 2–3 years of experience in system engineering, DevOps, or infrastructure support., • Strong hands-on experience with Kubernetes., • Proficiency in Python scripting., • Experience with Helm and Terraform., • Good knowledge of Linux systems and networking fundamentals., • Familiarity with Docker and cloud environments., • Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps., • Strong analytical and troubleshooting skills. Preferred Skills • Exposure to Azure, AWS or GCP., • Experience with monitoring tools like Prometheus, Grafana, Datadog, or ELK., • Understanding of infrastructure automation, containerization, and release management. Knowledge of security and access management best practices. Benefits • Comprehensive health coverage, including dental and vision, • 401(k) retirement plan, • Eligibility for annual performance bonuses

Job DescriptionCompany Description About StockStory VERSANT is an independent, publicly traded company that brings together powerhouse brands such as CNBC, MS NOW (formerly MSNBC), USA Network, Oxygen, E!, SYFY, and Golf Channel along with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. StockStory, now part of CNBC under VERSANT, is building the next generation of AI-powered equity research for individual investors. This is a chance to build products that can shape how millions of consumers understand markets and make investing decisions. We offer the best parts of a startup environment - small team, high ownership, fast execution, and room to experiment - with the backing and stability of VERSANT, an independent publicly traded media company. As an AI engineer, you will work on both an existing AI product with real user impact and greenfield projects with significant room for exploration. The work spans cutting-edge LLMs, large-scale data systems, financial reasoning, and research tooling, with opportunities to apply ideas from functional programming and graph-based systems where they create real advantage. You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design. For an ambitious AI engineer, it is an unusual opportunity to work with cutting-edge LLMs and advanced data systems while learning firsthand how sophisticated investors analyze businesses and markets. Job Description We're looking for a Staff AI Engineer to help build the next generation of AI-powered equity research. This role is for engineers who are excited by taking LLM capabilities beyond prototypes and turning them into robust product systems that deliver real value in production. It is especially well suited to people who enjoy designing end-to-end workflows, shaping technical direction, and building reusable foundations that help multiple teams move faster. You will design, build, and ship LLM-powered systems that integrate into new and existing workflows across the platform, spanning orchestration, retrieval, tool use, evaluation, and operational safeguards. You will also help define the engineering standards and architectural patterns that make these systems reliable, scalable, and maintainable over time. This role sits within a small and growing, high-caliber team where individuals are expected to operate with a high degree of ownership and autonomy, contributing directly to core product, infrastructure, and AI platform decisions while working closely with engineering and senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers. A genuine interest in investing, public markets, and fundamental business analysis is expected. What You'll Do: · Build end-to-end distributed agentic AI solutions that are reliable and scalable · Lead cross-functional initiatives requiring coordination across multiple teams and shared systems · Mentor other engineers and define quality standards and best practices · Own long-term maintainability, observability, and cost efficiency of AI systems · Monitor model quality drift, prompt alignment, alerting, and operational health Requirements: • Minimum of 5 years of experience in software engineering, with a strong track record of building and shipping production systems, • Proven experience designing and deploying LLM-based or GenAI systems in real-world applications, • Strong programming skills in Python and experience with modern backend architecture and distributed systems, • Understanding of LLM workflows, including prompting, tool use, retrieval-augmented generation (RAG), and evaluation methodologies, • Experience building scalable data pipelines and working with large, messy, or unstructured datasets, • Ability to design systems with strong observability, reliability, and performance characteristics in mind, • Experience working in cross-functional environments and leading technical projects end-to-end, • Strong problem-solving skills and ability to operate independently in ambiguous, fast-moving environments, • Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders, • Demonstrated interest in financial markets, investing, or business analysis Location: At CNBC Headquarters in Englewood Cliffs, NJ, you’ll have access to great perks and amenities: • Sweat it out -- Free onsite fitness center with state-of-the-art equipment, plus daily group classes, • Eat up -- Gourmet cafeteria with daily specials plus soup and salad bars, • Extras -- Dry cleaning, shoe shining and sneak peeks, • Don’t have a car? No problem! We offer free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City In addition to these benefits, employees in this group will be joining at a time of meaningful and continued investment in data, technology, and product development, with the opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time, offering meaningful exposure to senior leadership and the ability to influence how the platform evolves. Qualifications What We're Looking For: • Minimum of 5 years of experience in software engineering, with a strong track record of building and shipping production systems, • Proven experience designing and deploying LLM-based or GenAI systems in real-world applications, • Strong programming skills in Python and experience with modern backend architecture and distributed systems, • Understanding of LLM workflows, including prompting, tool use, retrieval-augmented generation (RAG), and evaluation methodologies, • Experience building scalable data pipelines and working with large, messy, or unstructured datasets, • Ability to design systems with strong observability, reliability, and performance characteristics in mind, • Experience working in cross-functional environments and leading technical projects end-to-end, • Strong problem-solving skills and ability to operate independently in ambiguous, fast-moving environments, • Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders, • Demonstrated interest in financial markets, investing, or business analysis Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to candidateaccessibility@versantmedia.com. VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc. VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.

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