AI Engineer

📋 Description

• Build agent loops and orchestration: tool use, structured outputs, business-rule enforcement
• Build the integration layer (via MCP) that lets agents securely call backend systems and business
• Render model output into live, streamed, accessible UI via generative-UI protocols
• Ground models in real data: retrieval, embeddings, and feedback loops that actually close
• Treat evals as a first-class system - provable improvement, not vibes
• Take a capability from prompt-in-a-notebook to a measured, guard-railed production feature

🎯 Requirements

• Shipped full-stack apps to production and owned them end-to-end: frontend through backend to deploy
• 5+ years shipping production software, 2+ building with LLMs in production (real users, not demos)
• Hands-on experience with UI protocols (A2UI, AG-UI, MCP-UI, or similar). You've built against a
• The AI spine: prompt/context engineering, agents, tool use, structured outputs, evals, MCP Python
• Working fluency with retrieval/embeddings and SQL

🎁 Benefits

• Comprehensive health benefits for you and your dependents, including access to OpenUp for
• Learning and development opportunities including an annual learning budget, access to self-paced
• Family Leave Plus gives you additional fully paid weeks of parental leave on top of
• Equity participation program allows you to share in our success