Senior Context Engineer

Requirements:
5-7 years of total engineering experience, with at least 2-3 years on production context pipelines, retrieval-augmented systems, or retrieval at scale.
Has shipped a production retrieval or context system and run the evaluations that prove it works.
Both halves are required; we will ask for the specific evaluation design and what it caught.
Hands-on builder. You can sit down and ship the evaluation framework yourself this week, not delegate it.
Strong systems thinker. Opinions on vectorisation choices, chunking strategy, retrieval ranking, hybrid search, and cost/latency trade-offs and the ability to defend them.
Has built or owned at least two integration connectors end-to-end (OAuth, rate limits, normalisation).
Comfortable in our stack: TypeScript, Node.js, PostgreSQL, vector storage (pgvector or equivalent).
Strong adjacent stacks accepted if the ramp story is credible.
Written communication strong enough to author RFCs that another engineer or an AI agent can build from without you in the room.
AI-augmented engineering as a first-class part of your loop.
If working through Claude (or equivalent) feels uncomfortable to you, this role is not a fit.
Smart and curious first-principles reasoning, comfortable in ambiguity, learns the next thing fast.
Bonus: experience with multimodal context (image or video embeddings, multimodal retrieval); has worked on agent / tool-calling systems and understands the evaluation question for tool calls; experience with multi-tenant context isolation; has worked with Model Context Protocol (MCP) servers; has mentored a junior engineer to ship-readiness.

Experience
5-7 yrs