Senior AI Product Engineer 2, Audit

What you'll do

• Build AI-powered product features end-to-end — React/TypeScript UI through Node.js/Python backend — with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns.
• Translate AI capabilities — RAG pipelines, agentic workflows, structured reasoning — into interactions that feel natural to compliance practitioners.
• Partner with AI Engineers to define API contracts and output schemas.
• Advocate for the user's perspective in technical decisions; surface where model outputs break down in practice and iterate the product layer accordingly.
• Build user-facing feedback loops that capture signal on AI output quality and make it actionable for the broader AI team.
• Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests that validate behavior across the full stack.
• Establish reusable patterns (streaming hooks, feedback components, AI state management) that accelerate future AI feature development.
• Mentor engineers newer to AI product development; participate in design reviews with both engineering depth and product instinct.

What you'll bring

• 7+ years of software engineering experience with a proven track record of shipping full-stack features in production; 2+ years working on AI-powered product features.
• Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gracefully.
• Solid Python, Node.js, and TypeScript skills; experience designing and consuming APIs that integrate with LLM providers, orchestration frameworks, or AI services.
• Hands-on experience building with LLM APIs (OpenAI, Anthropic, etc.); practical understanding of prompt engineering, context management, RAG, Quality/Evals (Braintrust or others), and structured outputs.
• Familiarity with agent frameworks (LangGraph, LangChain, custom runtimes) and how to build product surfaces on top of multi-step agentic workflows.
• Experience implementing streaming response patterns (SSE, WebSockets, chunked HTTP) and building UIs that handle progressive, partial, and uncertain outputs.
• Strong intuition for user experience; you ask "does this feel right to the user" as often as "does this work technically".
• Track record of working closely with AI/ML engineers, product managers, and designers; comfortable operating in a cross-functional product team where the requirements are often ambiguous and the iteration is fast.

Bonus Qualifications

• Experience in compliance, security, GRC, or other document-heavy enterprise domains.
• Experience with MCP (Model Context Protocol) or similar tool-use interfaces for AI agents.
• Exposure to RAG system design — not as an owner, but as a consumer who has debugged retrieval quality issues from the product layer.
• Experience building feedback and annotation tooling that captures user signal on AI output quality.