Principal Software Engineer, DGX Cloud Production Engineering
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 4
Communication @ 6
Distributed Systems @ 7
GPU @ 4
Go @ 7
HPC @ 4
Kubernetes @ 4
Leadership @ 6
Networking
Python @ 7
Rust @ 7
Technical Leadership @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking a principal-level software engineer to build the next generation of its Kubernetes platform. The team develops foundational capabilities for self-service GPU infrastructure, managed Kubernetes control planes, cluster operations, and automation for large-scale AI and improved computational environments.
The role works 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.
Responsibilities
- 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.
Requirements
- 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.
- 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++.
- Experience 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.
Preferred Qualifications
- Experience building Kubernetes platforms or managed Kubernetes services.
- Expertise in fleet management, cluster upgrades, node lifecycle, remediation, or day-2 operations.
- Experience with declarative infrastructure, Kubernetes controllers, GitOps, or policy-driven platform automation.
- Familiarity with both public-cloud and bare-metal infrastructure environments.
- Experience supporting AI, GPU, HPC, or other large-scale accelerated computing platforms.
Benefits
NVIDIA offers competitive salaries, equity, and a generous benefits package. The base salary range is USD 272,000–431,250, determined by location, experience, and the pay of employees in similar positions.
Applications for this job will be accepted at least until August 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment and maintaining equal employment opportunity.