Principal SRE

Job Overview As a Principal SRE at NVIDIA, you will shape the technical direction of NVIDIA's AI Platform Runtime and lead reliability engineering initiatives spanning multiple organisations. You will solve complex, ambiguous problems at enterprise scale, establish architectural standards, and influence how teams design and operate critical AI-powered services. Responsibilities Define and drive the long-term technical vision, architecture, and roadmap for reliability across NVIDIA's AI Platform Runtime and related enterprise systems. Architect highly available, resilient, secure, and scalable distributed platforms that power NVIDIA's next-generation AI-driven products and services. Lead the design and development of AI agents, AI skills, and intelligent automation that accelerate platform operations, incident response, troubleshooting, and remediation. Establish platform-wide reliability standards, including service-level objectives, error budgets, capacity models, resilience patterns, and operational readiness requirements. Identify systemic risks and lead cross-functional programs that improve availability, scalability, performance, security, and developer productivity. Advance observability across complex distributed environments through OpenTelemetry, metrics, logs, traces, profiling, analytics, and automated anomaly detection. Partner with senior leaders and engineers across Cloud, Platform, Security, Networking, and AI/ML organisations to make high-impact architectural and investment decisions. Provide technical leadership during critical incidents and ensure that lessons from incidents translate into durable engineering and organisational improvements. Develop reference architectures, shared platform capabilities, and automation frameworks that can be adopted across multiple engineering organisations. Influence, mentor, and raise the technical bar for senior engineers and technical leaders throughout the company. Requirements 15+ years of experience in Site Reliability Engineering, Platform Engineering, Distributed Systems, Cloud Architecture, or related infrastructure engineering roles. BS or MS degree in Computer Science or a related technical field involving significant software development, or equivalent experience. Demonstrated experience setting technical strategy and leading large-scale engineering initiatives across multiple teams or organisations. Deep expertise in distributed systems architecture, networking, Linux, Kubernetes, and public cloud platforms such as AWS, Azure, or GCP. Strong proficiency in one or more programming languages such as Python, Go, TypeScript, JavaScript, or Java, with experience building production-grade automation and platform software. Extensive experience with infrastructure-as-code and platform automation technologies such as Terraform, Crossplane, AWS CDK, AWS CloudFormation, or equivalent tools. Deep understanding of observability at scale, including OpenTelemetry and modern metrics, logging, tracing, profiling, and analytics platforms. Expertise in reliability engineering practices, including service-level objectives, error budgets, capacity planning, fault tolerance, disaster recovery, incident management, and blameless postmortems. A track record of delivering measurable improvements in availability, performance, operational efficiency, or engineering productivity within complex environments. Outstanding technical judgment, communication, and collaboration skills, with the ability to influence senior stakeholders across technical and organisational boundaries. Nice to Have Experience designing or operating large-scale AI/ML platforms, GPU infrastructure, inference systems, training environments, or high-performance computing platforms. Hands-on experience building AI agents, agentic workflows, or intelligent automation for infrastructure and production operations. Demonstrated success establishing reliability architecture and engineering standards adopted across a large enter