Principal AI Engineer

- A track record of eval-driven product improvement: you have diagnosed agent or LLM behaviour from traces and user feedback, designed the evaluation that exposed the problem, shipped the fix and measured the outcome - Direct experience building agents with state and memory, and iterating on prompts, skills and tool behaviour safely in production - Familiarity with MCP, including exposing public MCP servers and tools - Experience designing telemetry for AI systems, and using it to make engineering and product decisions - 10+ years of software engineering experience, with the recent years spent shipping and operating AI-driven products on real production traffic, ideally products with public APIs and data models that had to evolve without breaking customers - Comfort working with data scientists, engineers, and product managers as peers, translating between measurement and shipping, and communicating trade-offs clearly - Experience running product experiments end to end: instrumentation, unattended execution, and interpreting results - A pragmatic, low-ego style suited to a distributed, async-first team - Experience building products with public APIs and evolving data models, and the judgement that comes with maintaining external contracts as a product changes - Strong backend engineering skills in either Python or TypeScript: APIs, stateful workflows, data pipelines and production services - Agentic retrieval experience, including knowledge representation - Experience with…