Senior Software Engineer, DGX Cloud Production Engineering

at Nvidia

USD 184,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI API ArgoCD @ 4 Communication @ 6 Debugging Distributed Systems @ 6 GPU @ 4 Go @ 7 Kubernetes @ 4 Linux @ 4 Networking Observability @ 4 Python @ 7 Security Terraform @ 4

Details

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. The production engineering team focuses on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments.

Responsibilities

Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) 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 bring-up, 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.

Requirements

8+ years of experience building or operating production infrastructure.
Strong programming skills in Python, Go, or similar languages.
Experience with Linux, Kubernetes, containers, cloud infrastructure, or infrastructure automation.
Ability to troubleshoot distributed systems in production.
Clear communication and the ability to work across teams.
BS/MS in Computer Science or equivalent experience.

Preferred Qualifications

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.

Compensation and Benefits

The base salary range is $184,000–$287,500 for Level 4 and $224,000–$356,500 for Level 5. Base salary is determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until July 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.