Principal Software Engineer, DGX Cloud Production Engineering

NVIDIA is seeking a principal-level software engineer to build the next generation of our Kubernetes platform.

Our teams build foundational capabilities for self-service GPU infrastructure, managed Kubernetes control planes, management of cluster operations, and automation for large-scale AI and improved computational environments.

In this role, you will work at the intersection of platform architecture and production-grade Kubernetes lifecycle systems.

You will lead technical strategy and execution for systems that make clusters easier to provision, upgrade, operate, and scale across cloud and on-premises environments.

What you will be doing:

Lead the architecture and development of core Kubernetes platform capabilities, including cluster management, control plane services, fleet lifecycle, and day-2 operations.

Design and build highly reliable distributed systems and APIs for provisioning, managing, upgrading, and remediating Kubernetes clusters at scale.

Define technical requirements, validation criteria, production-readiness practices, and the direction for declarative workflows and automation across the Kubernetes stack.

Collaborate across engineering teams to create cohesive platform experiences spanning management APIs, lifecycle orchestration, runtime integration, and fleet consistency.

Lead the diagnosis and resolution of complex platform issues spanning infrastructure, runtime, networking, hardware, and operations, improving the scalability, resilience, and operability of systems supporting large-scale AI deployments.

Influence engineering standards, architectural decisions, and long-term platform strategy.

Mentor senior engineers and raise the bar for design quality, execution, and engineering rigor across the organization.

What we need to see:

BS or MS degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.

15+ years of relevant software engineering experience, including experience building and operating large-scale production systems.

Deep expertise in Kubernetes internals, APIs, controllers or operators, and cluster lifecycle management.

A strong background in distributed systems design, reliability, scalability, and failure recovery.

Proven experience building platform software, infrastructure control planes, or foundations for managed services.

Strong programming skills in one or more systems or cloud-native languages, such as Go, Python, Rust, or C++.

designing clear APIs and abstractions for platform consumers and engineering teams.

Demonstrated ability to provide technical leadership across team boundaries and drive ambiguous, cross-functional initiatives to completion.

Excellent communication and collaboration skills, backed by a sustained record of significant technical contributions and recognized expertise influencing department-level architecture and high-priority company initiatives.

Ways to stand out from the crowd:

Experience building Kubernetes platforms or managed Kubernetes services.

Expertise in fleet management, cluster upgrades, node lifecycle, remediation, or day-2 operations.

with declarative infrastructure, Kubernetes controllers, GitOps, or policy-driven platform automation.

Familiarity with both public-cloud and bare-metal infrastructure environments.

supporting AI, GPU, HPC, or other large-scale accelerated computing platforms.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers.

We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: GPU, Cloud, Cloud Development or Distributed Cloud.

If you're a creative Principal Software Engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.