Senior Staff Site Reliability Engineer

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is looking for a Senior Staff Site Reliability Engineer to join our team in India. This is a senior individual-contributor role that combines real-time incident leadership with deep hands-on engineering, focused on how we detect, respond to, and prevent issues at scale across NVIDIA's AI-powered enterprise platforms. You will operate as an Incident Commander during critical events, set the technical direction for reliability engineering across multiple teams, and build the automation, observability, and AI-assisted tooling that reduce operational toil and raise reliability over time. You will also mentor and grow SRE talent as we scale the practice in India. What You'll Be Doing: Lead major incidents end to end — driving triage, cross-team coordination, decision making, and executive communication across global time zones. Set technical direction for SRE initiatives that improve reliability, scalability, and developer efficiency across NVIDIA's enterprise systems, and drive them to adoption beyond your immediate team. Design, build, and operate distributed systems — including Kubernetes-based and cloud-native infrastructure — that power NVIDIA's AI-powered enterprise products and services. Build automation for incident detection, triage, communication, and remediation, replacing manual runbooks with self-healing systems. Improve observability and signal quality to enable earlier detection, reduce alert noise, and eliminate reliance on user-reported issues. Drive root cause analysis and translate learnings into systemic fixes, automation, and prevention mechanisms; raise the bar on post-incident review quality across the org. Apply AI and data-driven techniques — LLMs, anomaly detection, signal correlation — to enhance incident triage, summarisation, and decision support. Champion AI-assisted engineering practices, including coding agents and LLM-powered tooling, to accelerate day-to-day engineering workflows. Partner with Cloud, Platform, Security, and AI/ML teams to embed SRE best practices, define SLOs and error budgets, and influence architecture early in the design cycle. Mentor engineers, raise engineering standards through design and code review, and help build a strong reliability culture in the India organisation. What We Need To See: