Principal AI Engineer - Context - Agents and Context

• 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.
• 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.
• Experience running product experiments end to end: instrumentation, unattended execution, and interpreting results.
• 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.
• Comfort working with data scientists, engineers, and product managers as peers, translating between measurement and shipping, and communicating trade-offs clearly.
• A pragmatic, low-ego style suited to a distributed, async-first team.

Bonus Points

• Experience with agent frameworks such as LangGraph, CrewAI, Claude Agent SDK, or similar.
• Agentic retrieval experience, including knowledge representation.
• Practical Elasticsearch experience.