Описание
We are looking for a Chief Forward Deployed Engineer to build AI-native solutions where LLM and its harness are the core of the value. This is a builder's role: you and your team are responsible for building agentic systems, writing the production code, and standing up the evals and observability. You will work closely with SMEs and end-users to understand where the real value lies, and you will design the feedback loops.
Responsibilities
Design, build, and ship AI-native systems E2E — agents, workflows, RAG, and the harness: custom tool calling, sandboxing, context engineering and sub-agents, caching, compaction Build the evaluation pipelines and use them to prove the system is genuinely useful Design for failure in the agent loop: retries, model fallbacks, cost limits, and human-in-the-loop on consequential actions Capture domain expertise and repeatable workflows — so what works on one engagement carries to the next Engage early, to help shape the use case and check technical feasibility Write production-grade Python: integrations, APIs, data access, deployment Work directly with SMEs and end-users — interviews, UAT, observing the real workflow — and validate that the system fits how people actually work
Requirements
7+ years of engineering experience, with a strong recent track record building production AI / LLM applications (not prototypes or research only) Strong agent-design judgment — task-harness fit, matching the harness to the context, failures, and policies of th
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