Senior AI Engineer, Agents & Search

About this role

We’re hiring an engineer to help build the intelligence behind Fetch: agents that understand recruiting context, retrieve the right information, use tools reliably, and move work forward.

You’ll own the systems around the model, from search, memory, and context assembly to agent execution and evaluation. You’ll work on problems where quality is visible in real interactions: whether an agent finds a relevant clinician, remembers their preferences, answers accurately, takes the right next step, or recognizes that a recruiter needs to help.

What you’ll build

- Agent harnesses and orchestration.
Design how agents reason, select tools, maintain state, recover from failures, and resume work across conversations and background workflows. Make deliberate decisions about model selection, execution limits, retries, and human handoffs.
- Search and retrieval.
Improve how Fetch finds and matches clinicians to opportunities. Combine structured criteria, unstructured information, and conversation history; experiment with query planning, semantic retrieval, and reranking to improve relevance.
- Tools that accomplish real work.
Give agents well-defined capabilities to search records, read CVs, collect missing information, schedule follow-ups, and interact with recruiting systems. Make those actions permission-aware, observable, and safe to retry.
- Context and memory.
Help agents use clinician preferences, relationship history, job details, and recruiter instructions effectively. Handle incomplete or conflicting information without losing track of what is known and where it came from.
- Evals and experimentation.
Build repeatable evaluations from real recruiting scenarios and production failures. Measure retrieval relevance, factual grounding, tool use, conversation quality, task completion, and appropriate handoffs alongside latency and cost.
- Debugging and developer tooling.
Build traces, replay tools, and experiment workflows that make...