Role at a glance
- Salary
- $272K – $431.3K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 15+ years of experience building and operating large-scale distributed systems or cloud infrastructure.
- Education
- BS/MS in Computer Science or equivalent experience.
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Role Summary
The role focuses on shaping the technical direction for DGX Cloud production engineering, Kubernetes-based operations, automation, and reliability across large-scale GPU clusters in NVIDIA Cloud Partner and on-prem environments. The engineer will lead architecture and software efforts that improve cluster lifecycle management, operational readiness, and reliability.
What You'll Do
- Define and execute the technical strategy for DGX Cloud cluster operations.
- Build automation, GitOps, and Day 2 reliability for large-scale GPU clusters.
- Design and implement systems for cluster lifecycle, validation, repair, upgrades, observability, and readiness.
- Establish patterns for Kubernetes-based GPU cluster operations across partner and on-prem environments.
- Identify and eliminate operational toil through software, APIs, automation, and agent-assisted workflows.
- Set technical standards for production readiness, SLOs, incident response, handoff gates, and operational acceptance.
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View full postingQualifications
Deep experience with Kubernetes, Linux, infrastructure automation, and production operations; strong programming experience in Go, Python, or similar; proven ability to lead complex cross-org technical initiatives; experience designing reliable systems with clear SLOs, observability, incident response, and automation.
Required
- 15+ years of experience building and operating large-scale distributed systems or cloud infrastructure
- Kubernetes
- Linux
- Infrastructure automation
- Production operations
- Go, Python, or similar
- Leading complex cross-org technical initiatives
- SLOs
Preferred
- GPU clusters
- AI/ML infrastructure
- Kubernetes operators
- GitOps
- BMaaS/VMaaS
- Managed Kubernetes
- Multi-cloud fleet operations
- Internal platforms
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA DGX Cloud is scaling GPU infrastructure across internal, partner, and cloud environments. We are looking for Principal Software Engineers to help shape the technical direction for production engineering, Kubernetes-based operations, automation, and reliability across large-scale GPU clusters.
This role is for senior technical leaders who can define architecture, lead through influence, build critical systems, and turn ambiguous infrastructure problems into durable software and operating models.
What you’ll be doing:
Define and execute the technical strategy for DGX Cloud cluster operations, building the automation, GitOps, and Day 2 reliability needed to operate large-scale GPU clusters across NVIDIA Cloud Partners (NCPs) and on-prem environments.
Lead design and implementation of systems for cluster lifecycle, validation, repair, upgrades, observability, and readiness.
Establish patterns for Kubernetes-based GPU cluster operations across partner and on-prem environments.
Identify and eliminate operational toil through software, APIs, automation, and agent-assisted workflows.
Set technical standards for production readiness, SLOs, incident response, handoff gates, and operational acceptance.
Mentor engineers and influence platform, infrastructure, storage, networking, security, and workload teams.
What we need to see:
15+ years of experience building and operating large-scale distributed systems or cloud infrastructure.
Deep experience with Kubernetes, Linux, infrastructure automation, and production operations.
Strong programming experience in Go, Python, or similar.
Proven ability to lead complex cross-org technical initiatives.
Experience designing reliable systems with clear SLOs, observability, incident response, and automation.
BS/MS in Computer Science or equivalent experience.
Ways to stand out from the crowd:
Experience with GPU clusters, AI/ML infrastructure, Kubernetes operators, GitOps, BMaaS/VMaaS, managed Kubernetes, or multi-cloud fleet operations.
Experience building internal platforms, control planes, lifecycle automation, or production readiness frameworks.
Track record of turning operational pain into reusable software, APIs, and engineering standards.
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hard-working people on the planet working for us. If you're creative, hard-working and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.