AI Product Engineer, Evidence

Why Join The Drata Team? The best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide , united by a culture that values trust, speed, and continuous growth. Hear the Voice of the Team : Explore our "Life at Drata" page for employee testimonials on our collaborative and the growth opportunities available. Connect with Us on Socials: LinkedIn - follow us for company updates, employee stories, and career news. Job Summary: Drata 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'll translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences — streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that makes compliance feel effortless. You'll partner closely with AI Engineers who own the backend intelligence and Product and Design who shape the vision, but you are the engineer who closes the loop between AI capability and the customer experience. 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; translate RAG pipelines, agentic workflows, and structured reasoning into interactions that feel natural to 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 both engineering depth and product instinct What you'll bring: Experience: 3+ years of software engineering experience with a proven track record of shipping full-stack features in production; 1+ years working on AI-powered product features Frontend: Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gracefully Backend: Solid Python and Node.js and Typescript 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(Braintrust or others) and structured outputs — not just calling an endpoint, but knowing what makes a prompt reliable in production Familiarity with agent frameworks (LangGraph, LangChain, 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, WebSockets, 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 ambigous 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 Impact This role is the bridge between Drata's AI ambitions and the customers who will benefit from them. Your work will: 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 actually trust and use Accelerate the vel