Own end-to-end delivery of software-engineering data programs, including scope, timelines, quality, throughput, cost, contributor performance, and customer reporting. Coordinate hundreds of distributed engineers, optimize annotation and evaluation workflows, analyze quality data, build automation and reusable playbooks, and serve as the primary client contact for AI research organizations. The role requires technical fluency sufficient to inspect code, tests, workflows, and evaluation results while leading large-scale operational execution.

Set technical direction across multiple services and teams; lead cross-cutting initiatives like migrations and modernization; own reliability and performance at scale; raise engineering standards through design docs and reviews; mentor senior engineers and partner with leadership on technical roadmaps.

Lead end-to-end design, build, and production operation of scalable distributed systems. Debug production issues, improve reliability and performance, conduct code reviews, mentor junior engineers, and collaborate cross-functionally to deliver high-quality software at scale with an AI-forward mindset.