Lead AI Engineer

We're looking for a Lead AI Engineer to own the backend and Agent systems behind our LLM-powered products. The role is end-to-end: you'll build the Agent workflows, define how we measure quality, keep them reliable in production, and shape where the product goes next.

This role is for someone who has shipped LLM features to real users, stayed with them after launch, and can prove with data that their changes made things better.

Job Scope:

Build and own AI backend and Agent workflows

• Design, build, and maintain multi-turn conversation systems, including context management, tool calling, knowledge retrieval (RAG), state management, and human handoff.

Drive evaluation and continuous improvement

• Define success criteria with Product, Design, and QA leads.

• Turn production failures into evaluation samples and regression tests.

• Measure the impact and side effects of every change before and after release.

Diagnose problems across the stack

• Isolate the root cause of failures: model judgment, knowledge gaps, abnormal tool responses, backend instability, or conflicting rules.

• Apply the right fix for each cause rather than defaulting to prompt tweaks.

Own production reliability

• Handle timeouts, retries, graceful degradation, async jobs, and third-party dependency failures.

• Make sure every issue is traceable through logs, every change is versioned, and every failure has a recovery path.

Shape product and technical decisions

• Give clear, reasoned positions on requirements, covering feasibility, cost, risk, and alternatives.

• Propose better approaches and break work into phased, shippable deliverables.

Communicate proactively and follow through

• Share progress, blockers, ETAs, and next checkpoints without needing to be chased.

• After launch, track real-world impact and leave clear documentation and handover materials.