Lead Engineer, AI Quality

Circle's AI Quality team owns the foundation for measuring, diagnosing and improving the quality of the AI features in its platform. The posting draws the boundary clearly: this is production AI systems work, not ML research or model training.

Concretely that means evaluation infrastructure. The CI/CD pipelines, scorers and datasets that establish whether Circle's agents, planners, tool-callers and sub-agents are actually working, from a single tool call up to a full multi-turn conversation. Then the diagnostic tooling to locate where quality breaks down, across plan creation against execution, tool selection, and tool trajectory in the harder areas like workflows, site builder and analytics. It is described as a hands-on player-coach role, so it includes leading and managing the team.

Circle is fully remote, around 270 people across more than 30 countries, does not track hours, and benchmarks compensation to the US wherever you live. It publishes this one as a single annual figure rather than a range. Remote from Europe, the Middle East, Africa or Asia-Pacific.