NVIDIA
Artificial Intelligence, High-Performance Computing, Visualization, Cloud Infrastructure
PrincipalSoftwareEngineer,DGXCloudProductionEngineering
Neural analysis suggests this role is
optimal for Lead candidates.
“Principal Software Engineer, DGX Cloud Production Engineering at NVIDIA. Skills: Kubernetes, production engineering, automation, reliability, large-scale distributed systems, cloud infrastructure, Go, Python. 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”
What You'll Achieve.
building the automation, GitOps, and Day 2 reliability needed to operate large-scale GPU clusters; Establish patterns for Kubernetes-based GPU cluster operations; Set technical standards for production readiness, SLOs, incident response, handoff gates, and operational acceptance
Industry & Context.
turn ambiguous infrastructure problems into durable software and operating models; Identify and eliminate operational toil
What They're Looking For.
Must Have
15+ years of experience building and operating large-scale distributed systems or cloud infrastructure, Deep experience with Kubernetes, Linux, infrastructure automation, and production operations, 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
Nice to Have
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
What You'll Do.
Define and execute the technical strategy for DGX Cloud cluster operations
building the automation
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
Establish patterns for Kubernetes-based GPU cluster operations across partner and on-prem environments
Identify and eliminate operational toil through software
and agent-assisted workflows
Set technical standards for production readiness
and operational acceptance
How You'll Work.
Team & Collaboration
Mentor engineers and influence platform, infrastructure, storage, networking, security, and workload teams
Process & Methodology
Lead complex cross-org technical initiatives
Full Job Description
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 Ku
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