Build, test, and deploy production-ready ML services and data workflows on GCP. Implement clean, tested code, CI/CD, and monitoring; create evaluation pipelines and metrics; troubleshoot reliability and latency; and collaborate with product, operations, and engineering stakeholders to deliver end-to-end ML features.

Process and validate provider credentials, licenses, and payor enrollments; research licensure and CME rules; complete applications; communicate with providers and clients; support implementations and draft clear guideline documents.

Build and maintain scalable, production-grade systems; own end-to-end feature delivery; influence architecture; improve reliability, performance, and code quality; collaborate with product; participate in on-call and incident response; follow security best practices for sensitive data.