# AI Product Engineer, Evidence

**Company:** [Drata](https://hotfix.jobs/companies/drata)
**Location:** San Francisco, CA
**Role:** Fullstack Engineering
**Experience:** 3+ years
**Skills:** React, TypeScript, Python, Node.js, LLM APIs, RAG, LangChain, LangGraph, Prompt Engineering, Streaming (Sse/Websockets), API Design, Ai Product Development
**Posted:** 2026-05-26

> Own full-stack development of customer-facing AI features (React/TypeScript UI + Node/Python backend) including streaming chat, agentic workflows, and RAG interfaces. Partner with AI engineers and PMs to deliver intuitive compliance product experiences.

## Job Description

## Responsibilities
- 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
- Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests
- 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

## Requirements
- 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
- Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data
- Solid Python and 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, 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; track record of working closely 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 tool-use interfaces for AI agents
- Exposure to RAG system design 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

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