Principal Site Reliability Engineer
About The Position
Site Reliability Engineering at NVIDIA focuses on designing, building, and operating large-scale production systems with efficiency, resilience, and availability. It combines software and systems engineering with expertise in distributed systems, networking, cloud infrastructure, Kubernetes, databases, capacity management, continuous delivery, and observability. NVIDIA SREs ensure services meet reliability and performance objectives while enabling safe, rapid software delivery, automating operational work, improving performance, and strengthening production reliability. The Principal SRE will shape the technical direction of NVIDIA’s AI Platform Runtime and lead reliability initiatives across multiple organizations. The role involves solving complex, ambiguous problems at enterprise scale, establishing architectural standards, and influencing the design and operation of critical AI-powered services. The Principal SRE will also advance AI agents and skills to transform platform operations and developer productivity, while fostering collaboration, curiosity, and learning through blameless analysis.
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 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, 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.
- 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 organizational boundaries.
Nice To Haves
- 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 enterprise.
- Experience applying machine learning, analytics, or advanced automation to capacity management, anomaly detection, incident response, or autonomous remediation.
- Recognized technical leadership through patents, publications, open-source contributions, industry standards, conference presentations, or widely adopted internal platforms.
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 for AI-driven products and services.
- Lead the design and development of AI agents, AI skills, and intelligent automation for 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 to improve availability, scalability, performance, security, and developer productivity.
- Advance observability across 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 organizations on architectural and investment decisions.
- Provide technical leadership during critical incidents and ensure incident lessons lead to durable engineering and organizational improvements.
- Develop reference architectures, shared platform capabilities, and automation frameworks for adoption across engineering organizations.
- Influence and mentor senior engineers and technical leaders throughout the company.
Benefits
- Eligible for equity and benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
