Lead AI Native Engineer

What you'll do

• Build and ship end-to-end agents for workflows across research, software, hardware, data, and operations; create reusable agent infrastructure and trusted-data integrations.
• Develop evaluations, regression tests, tracing, monitoring, and failure-analysis systems to improve agent quality, reliability, security, latency, and cost.
• Set technical architecture and engineering standards, review designs and code, and support strategic initiatives with agents and analytical systems.

What they ask for

• 5+ years in software engineering, applied AI, ML systems, or a related field.
• Experience at a frontier AI lab, leading AI company, or comparable team working at the edge of current model capabilities.
• Track record shipping production agentic systems used by real users; deep experience with frontier model APIs, tool use, orchestration, context engineering, retrieval, memory, and multi-step workflows.
• Experience evaluating and monitoring AI systems, plus fluency with AI-native development workflows; requires 5 days/week in-office collaboration.

Nice to have

• Experience with post-training, model evaluation, inference, or research infrastructure at a frontier lab or model company.
• Experience with MCP infrastructure, developer platforms, knowledge graphs, RAG, secure enterprise integrations, robotics, autonomous systems, or industrial automation.

Tools

Claude Code, Codex, Cursor, MCP

AI focus

Builds production agents and shared agent foundations, evaluates frontier models and agent tools, and applies agents and analytical systems to company workflows and strategic decisions.