Ownership of reliability, monitoring, and incident response for AI infrastructure. Build automation and tooling for CI/CD and Kubernetes, extend deployment frameworks, integrate security tooling, improve observability and documentation, and develop internal full-stack tools in Go or Python. Provide on-call support, lead RCA and blameless retros, and drive measurable reliability improvements.

Lead ML data and feature strategy for fraud detection, owning end-to-end feature engineering pipelines, validating feature quality at scale, and partnering with ML engineers to productionize, monitor, and improve models. Drive roadmap to close infrastructure gaps, mentor junior team members, and translate ML findings into business-impacting decisions to prevent account takeover and scam activity.