Principal Generative AI Engineer

Hands-on, full-stack Generative AI role designing, building, and delivering AI solutions end to end across ML, Generative AI, and Agentic AI.

Responsibilities

• Design, build, and deliver AI solutions end to end across traditional ML, Generative AI, and Agentic AI, including shaping technical strategy and mentoring/managing a growing team.
• Scope and deliver core AI solutions in close partnership with business stakeholders, data scientists, engineers, and product and technology partners.
• Contribute to enterprise AI practices and standards, leveraging deep expertise in AI solution delivery.
• Own solution delivery on top of the enterprise AI platform, shipping agentic solutions end to end instead of building underlying platform infrastructure.
• Partner with the business to assess and quantify overall value delivered by the AI solution.

Requirements

• MS or PhD in Computer Science, AI, Engineering, Mathematics, or a related quantitative field.
• 8+ years applying data science, ML, and AI to real-world business problems, with increasing scope, complexity, and influence.
• Fluency with AI-assisted engineering tools (use daily) such as Codex and Claude Code, plus critical review of generated output.
• Experience building engineering agents that accelerate delivery itself, including testing, code review, or deployment-validation agents.
• Full-stack AI fluency across the spectrum from statistical modeling and ML to LLM application development and agentic system design.
• Ability to prototype and ship production solutions, including rapid prototyping tools such as Streamlit and React, with solution ownership through production.
• Strong Python software engineering skills.
• Working knowledge of SQL and JavaScript/TypeScript sufficient to build and ship a solution front end (for example, using React).
• Comfort with modern software practices: testing, code review, and CI/CD.
• Working fluency with containers and deployment operations, including Docker and Kubernetes, sufficient to independently ship and operate solutions on the platform (not to build or own platform infrastructure).
• Hands-on experience with LLMs, RAG architectures, and prompt engineering, including GraphRAG and knowledge graphs alongside vector-based RAG.
• Hands-on experience with multi-agent and sub-agent orchestration frameworks such as LangGraph or Google ADK (or equivalent), plus MCP (or equivalent) tool integration protocols for production agentic systems.
• Experience developing and evaluating AI systems with rigor, including automated evaluation pipelines, red-teaming, hallucination detection, safety testing, and performance monitoring.
• Proficiency with cloud AI platforms, especially GCP Vertex AI for agentic development, with working knowledge of AWS (SageMaker, Bedrock) and modern data platforms like Databricks.
• Comfort consuming cloud-native services and workflows (including existing IaC templates, CI/CD pipelines, and the AI gateway) to deploy and operate solutions.
• Strong stakeholder engagement and communication skills, including scoping initiatives, presenting to senior leaders, managing expectations, and driving alignment across business and technology partners.
• Track record of mentoring and elevating technical talent.
• Plus: experience in life insurance, financial services, or other regulated industries.

Location and Compensation

• Location: Weehawken, NJ (onsite)
• Compensation: USD 75 per hour

Technologies

• Codex, Claude Code
• Streamlit, React
• Python, SQL, JavaScript, TypeScript
• CI/CD
• Docker, Kubernetes
• LLMs, RAG, GraphRAG, knowledge graphs
• LangGraph, Google ADK, MCP
• GCP Vertex AI, AWS, SageMaker, Bedrock
• Databricks
• IaC, AI gateway