Senior Software Engineer, DGX Cloud Production Engineering
About The Position
NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. The Senior Software Engineer will join a production engineering team focused on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments. The team focuses on bare-metal infrastructure. The role involves building and operating automation for large-scale GPU clusters across NVIDIA Cloud Partners and on-premises environments, and developing tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations. The engineer will improve Day 0, Day 1, and Day 2 workflows for cluster bringup, handoff, and production operations; reduce manual production work through APIs, GitOps, automation, and agent-assisted workflows; participate in on-call and incident response; and partner with platform, storage, networking, security, and workload teams to prepare infrastructure for production.
Requirements
- 8+ years of experience building or operating production infrastructure.
- Strong programming skills in Python, Go, or similar.
- Experience with Linux, Kubernetes, containers, cloud infrastructure, or infrastructure automation.
- Ability to troubleshoot distributed systems in production.
- BS/MS in Computer Science or equivalent experience.
- Experience managing GPU fleets.
- Expertise in BMS and power management.
- Experience working with datacenter inventory management systems such as NetBox, Nautilus, or others.
Nice To Haves
- Experience with GPU infrastructure, Kubernetes operators, GitOps, Terraform, ArgoCD, or fleet automation.
- Experience with SLOs, on-call, incident response, observability, and reliability practices.
- Exposure to BMaaS, VMaaS, managed Kubernetes, or multi-cloud infrastructure.
- History of involvement with automated break-fix solutions at scale.
- Familiarity with handling a message bus and workflow engine.
Responsibilities
- Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners and on-premises environments.
- Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations.
- Improve Day 0, Day 1, and Day 2 workflows for cluster bringup, handoff, and production operations.
- Reduce manual production touches through APIs, GitOps, automation, and agent-assisted workflows.
- Participate in on-call, incident response, debugging, and durable follow-up work.
- Partner with platform, storage, networking, security, and workload teams to make infrastructure production-ready.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
