Build and scale a distributed platform supporting engineering simulations, agentic applications, and physical AI workflows. Responsibilities include designing distributed architecture, developing production Python services, optimizing distributed compute, implementing workflow orchestration, and contributing to CI/CD, testing, deployment, observability, reliability, and incident response. The role also involves mentoring engineers, making technical decisions, collaborating cross-functionally, interviewing candidates, and supporting end-to-end platform operations.

Lead the architectural evolution of an AI platform from monolithic to distributed systems. Design agent-ready services, write production Python, build distributed compute and workflow orchestration, and own CI/CD, testing, deployment, observability, reliability, and scaling. Mentor engineers, establish technical standards, guide cross-team decisions, collaborate with stakeholders, and support hiring. The role requires deep distributed systems, Kubernetes, AWS, workflow orchestration, data processing, security, and production reliability expertise.