Principal Site Reliability Engineer

What you'll do

• Define and drive the long-term technical vision, architecture, and roadmap for NVIDIA’s AI Platform Runtime.
• Architect highly available, resilient, secure, and scalable distributed platforms for next-generation AI products.
• Lead the design and development of AI agents and intelligent automation to accelerate platform operations and incident response.
• Establish platform-wide reliability standards including service-level objectives, error budgets, and capacity models.
• Advance observability across complex distributed environments using OpenTelemetry, metrics, logs, traces, and automated anomaly detection.
• Identify systemic risks and lead cross-functional programs to improve availability, performance, and developer productivity.
• Provide technical leadership during critical incidents and translate lessons into durable engineering improvements.
• Develop reference architectures and automation frameworks for adoption across multiple engineering organizations.

What we're looking for

• 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 organizations.
• 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 for building production-grade automation.
• Extensive experience with infrastructure-as-code and platform automation technologies such as Terraform, Crossplane, AWS CDK, or AWS CloudFormation.
• Deep understanding of observability at scale, including OpenTelemetry and modern metrics, logging, tracing, profiling, and analytics platforms.
• Expertise in reliability engineering practices including SLOs, error budgets, capacity planning, fault tolerance, disaster recovery, and incident management.