NVIDIA
GPU infrastructure
EngineeringManager,DGXCloudProductionEngineering
Neural analysis suggests this role is
optimal for Manager candidates.
“Engineering Manager, DGX Cloud Production Engineering at NVIDIA. Skills: Kubernetes-based operations, automation, reliability, cluster lifecycle tooling, production infrastructure, cloud platforms, distributed systems, reliability engineering, observability, incident response. Lead a team of software and production engineers building and operating DGX Cloud infrastructure. Drive execution across cluster operations, Kubernetes operability, automation, GitOps, observability, and incident response”
What You'll Achieve.
reducing toil; improving SLOs; turning operational work into software-driven systems
Industry & Context.
sound judgment in fast-moving environments
on-call, incident review
What They're Looking For.
Must Have
8+ overall years of industry experience, 2+ years leading or managing engineers, Experience building or operating production infrastructure, cloud platforms, Kubernetes environments, or distributed systems, understanding of reliability engineering, automation, observability, incident response, and operational excellence, Ability to work across teams and influence without direct authority, Clear communication, prioritization, and sound judgment in fast-moving environments, BS/MS in Computer Science or equivalent experience
Nice to Have
Experience leading SRE, production engineering, infrastructure automation, or platform teams, Experience with GPU infrastructure, Kubernetes fleet operations, GitOps, BMaaS/VMaaS, managed Kubernetes, or multi-cloud environments, Track record of reducing toil, improving SLOs, and turning operational work into software-driven systems
What You'll Do.
Lead a team of software and production engineers building and operating DGX Cloud infrastructure
Drive execution across cluster operations
Kubernetes operability
and incident response
Help define team priorities
and operational ownership
Build a healthy on-call and incident review culture
grow technical leaders
and create clear ownership across ambiguous problem spaces
How You'll Work.
Team & Collaboration
Partner with platform, workload, storage, networking, security, and TPM teams to improve production readiness; Ability to work across teams and influence without direct authority
Communication Scope
Clear communication
Process & Methodology
Help define team priorities, roadmap, staffing, and operational ownership
Full Job Description
NVIDIA DGX Cloud is building the operating model for reliable, scalable GPU infrastructure across internal, partner, and on-prem environments. We are looking for an Engineering Manager to lead a team of software and production engineers focused on Kubernetes-based operations, automation, reliability, and cluster lifecycle tooling. This leader will help run today’s production systems while building the automation and engineering practices needed for the next generation of DGX Cloud infrastructure. **What you’ll be doing:** * Lead a team of software and production engineers building and operating DGX Cloud infrastructure across NVIDIA Cloud Partner (NCP) and on-prem environments. * Drive execution across cluster operations, Kubernetes operability, automation, GitOps, observability, and incident response. * Help define team priorities, roadmap, staffing, and operational ownership. * Partner with platform, workload, storage, networking, security, and TPM teams to improve production readiness. * Build a healthy on-call and incident review culture focused on learning, ownership, and durable fixes. * Coach engineers, grow technical leaders, and create clear ownership across ambiguous problem spaces. **What we need to see:** * 8+ overall years of industry experience, including 2+ years leading or managing engineers. * Experience building or operating production infrastructure, cloud platforms, Kubernetes environments, or distributed systems. * Strong understanding of reliability engineering, automation, observability, incident response, and operational excellence. * Ability to work across teams and influence without direct authority. * Clear communication, strong prioritization, and sound judgment in fast-moving environments. * BS/MS in Computer Science or equivalent experience. **Ways to Stand Out:** * Experience leading SRE, production engineering, infrastructure automation, or platform teams. * Experience with GPU infrastructure, Kubernetes fleet operations, GitOps, BMaa
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