Senior Software Engineer, DGX Cloud Production Engineering

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Software EngineerSoftware Engineering

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Quick Summary

Key Responsibilities

Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments. Develop tools and services for provisioning, validation, upgrades, monitoring,

Requirements Summary

8+ years of experience building or operating production infrastructure. Strong programming skills in Python, Go, or similar. Experience with Linux, Kubernetes, containers, cloud infrastructure,

Technical Tools

Software EngineerSoftware Engineering

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling, and operational systems that make GPU clusters reliable, scalable, and safe to run. This role is part of a production engineering team focused on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments.

Responsibilities

~1 min read

→Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments.
→Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations.
→Improve Day 0 / Day 1 / 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.
→Team focused on bare-metal infrastructure

Requirements

~1 min read

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 & Power management.
Experience working with Datacenter Inventory Management Systems like Netbox, Nautilus, or others

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

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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 17, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.