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Senior AI Product Engineer, Agent Governance
Job in
San Francisco, San Francisco County, California, 94199, USA
Listed on 2026-06-02
Listing for:
Cacheflow
Full Time
position Listed on 2026-06-02
Job specializations:
-
Software Development
AI Engineer, Full Stack Developer
Job Description & How to Apply Below
Location
Hybrid – San Francisco
Employment TypeFull time
Location TypeHybrid
DepartmentEngineering
Job SummaryDrata is reimagining compliance as an intelligent, always‑on experience — and AI is at the center of that vision. We are seeking a Senior AI Product Engineer to own the full‑stack development of customer‑facing AI features, embedded directly within our product teams. This is not a platform or infrastructure role; you will translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences such as streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that make compliance feel effortless.
Responsibilities- Build AI‑powered product features end‑to‑end – React/Type Script 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; bring RAG pipelines, agentic workflows, and structured reasoning into natural interactions for compliance practitioners
- 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 engineering depth and product instinct
- Experience: 5+ years of software engineering with a proven track record of shipping full‑stack features to production; 2+ years working on AI‑powered product features
- Frontend: Strong proficiency in React and Type Script; experience building responsive, interactive UIs that handle async, streaming, and real‑time data gracefully
- Backend: Solid Python and Node.js and Type Script skills; experience designing and consuming APIs that integrate with LLM providers, orchestration frameworks, or AI services
- AI Fluency: Hands‑on experience building with LLM APIs (OpenAI, Anthropic, etc.); practical understanding of prompt engineering, context management, RAG, quality/evals tools, and structured outputs – not just calling an endpoint, but knowing what makes a prompt reliable in production
- Familiarity with agent frameworks (Lang Graph, Lang Chain, custom runtimes) and how to build product surfaces on top of multi‑step agentic workflows
- Streaming & Real‑Time UI: Experience implementing streaming response patterns (SSE, Web Sockets, chunked HTTP) and building UIs that handle progressive, partial, and uncertain outputs
- Product Sense: Strong intuition for user experience; you ask "does this feel right to the user" as often as "does this work technically" — and you’re right about both
- Collaboration: 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
- 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
- Define the standard for how AI features look, feel, and behave across Drata's product – setting a bar that the entire product engineering organization will build to
- Make compliance practitioners more capable and confident by turning AI intelligence into product interactions they…
Position Requirements
10+ Years
work experience
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