Senior DevOps Engineer

NVIDIA is looking for an exceptional engineer to grow and thrive alongside our HPC Infrastructure team that designs, evaluates, and optimizes the compute inrastructure powering NVIDIA's next-generation silicon design and AI workloads. You will own the automation platform underneath VLSI infrastructure - the tooling, services and pipelines that turn manual infrastructure work into something that runs itself What you'll be doing: - In this position, you will own the automation platform underneath VLSI infrastructure - the tooling, services and pipelines that turn manual infrastructure work into something that runs itself. - Design and build internal services and command-line tooling used daily by design and infrastructure engineers, with real attention to interface design and reliability. - Build event-driven automation around source control - reacting to repository events, keeping workspaces and client mappings healthy, and removing the manual maintenance around them. - Own CI, release and deployment mechanics for the team's internal tooling, and instrument what you build so it is observable and debuggable by the rest of the team. - This is a hands-on technical role. You will write and run the code yourself, work with the scheduling team on the automation layer beneath job submission, and reduce the operational load on senior engineers by turning their recurring manual work into services. What we need to see: - B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or equivalent experience. - 8+ years in DevOps, platform, or infrastructure software engineering. - Strong software engineering in Python - you write production-quality, tested code rather than one-off scripts, and you have delivered tooling that other engineers depend on daily. - Hands-on experience automating against source control management at scale, Perforce preferred and Git acceptable, including its APIs and event streams. - Solid CI/CD experience (GitLab CI, Jenkins, or equivalent) and container-based packaging and deployment. - Strong Linux systems knowledge and shell fluency, with experience building and operating internal developer platforms or engineering tooling. - Familiarity with batch compute environments and how engineering workloads are submitted, tracked and debugged, and comfort owning what you build in production. Semiconductor/EDA or HPC exposure is a plus.