Senior Software Engineer, AI Evaluation Infrastructure

• Design and ship features end to end: data model, API, background workers, and the UI when the change needs it.
• Build and improve how agents and models are evaluated: running trials in sandboxed environments, scoring results, and turning thousands of runs into results people can trust.
• Improve how benchmark tasks are quality-checked: verifiers, rubric-based and LLM-as-a-judge grading, and deciding whether a task is clear, solvable, and fair to score.
• Integrate new models, agents, and benchmarks in a way that generalizes, without a special case for each one.
• Keep the system fast and reliable as usage grows: efficient queries, safe migrations, and concurrency that holds up under load.