Senior AI Product Engineer, Frameworks

Responsibilities

• Build AI-powered product features end-to-end, from React/TypeScript interfaces through Node.js/Python backends.
• Implement real-time streaming, graceful degradation, and human-in-the-loop interaction patterns.
• Translate RAG pipelines, agentic workflows, and structured reasoning into intuitive product experiences.
• Partner with AI Engineers to define API contracts and output schemas.
• Advocate for users, identify where model outputs fail in practice, and iterate on the product layer.
• Build feedback loops that capture AI output-quality signals and make them actionable.
• Instrument AI features with product observability for latency, engagement, task completion, and drop-off.
• Create integration and end-to-end tests across the full stack.
• Establish reusable patterns for streaming hooks, feedback components, and AI state management.
• Mentor engineers and participate in engineering and product design reviews.

Requirements

• 5+ years of software engineering experience shipping full-stack production features.
• 2+ years working on AI-powered product features.
• Strong React and TypeScript proficiency.
• Solid Python and Node.js skills.
• Experience designing and consuming APIs integrating with LLM providers, orchestration frameworks, or AI services.
• Hands-on experience with LLM APIs such as OpenAI or Anthropic.
• Practical understanding of prompt engineering, context management, retrieval-augmented generation (RAG), quality/evaluation systems, and structured outputs.
• Familiarity with agent frameworks such as LangGraph, LangChain, or custom runtimes.
• Experience implementing streaming response patterns including SSE, WebSockets, or chunked HTTP.
• Experience building UIs for progressive, partial, and uncertain outputs.
• Strong product sense and user-experience judgment.
• Experience collaborating with AI/ML engineers, product managers, and designers.

Nice-to-haves

• Experience in compliance, security, GRC, or other document-heavy enterprise domains.
• Experience with MCP (Model Context Protocol) or similar AI-agent tool-use interfaces.
• Exposure to RAG system design and debugging retrieval-quality issues from the product layer.
• Experience building feedback and annotation tooling for AI output quality.

Compensation and Benefits

• Base salary: $150,000–$230,000 annually.
• Stock equity.
• Employer-paid medical, dental, and vision coverage.
• 401(k), life and disability insurance, and tax-advantaged spending accounts.
• Paid parental leave and fertility and family-building benefits.
• Professional and personal development stipends.
• Flexible vacation policy and paid holidays.