Applied AI Engineer

Own the implementation, testing, and delivery of defined AI components within an established system design.

Build agent tools, model integrations, and the backend services and APIs they depend on.

Run and extend evaluations within an established framework, interpret results, investigate common failure modes, and flag regressions.

Debug production issues in the components you own and resolve them using the team's engineering practices.

Experience building and shipping production software, with proficiency in Python and working knowledge of at least one of TypeScript, Java, or C++.

Hands-on experience integrating models or AI/ML components into a production application, such as calling LLMs, building retrieval or agent tooling…

A working understanding of ML evaluation: how to read results, spot regressions, and identify common causes of model failure.

Experience owning a defined piece of work through testing, release, and production debugging.