Software Engineer, SRE and Production Engineering - DGX Cloud

NVIDIA is hiring a Software Engineer, SRE and Production Engineering - DGX Cloud in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on Level.

AI in this role

Builds large-scale GPU infrastructure and automation software for AI workloads on NVIDIA DGX Cloud.

gopythonkubernetesredfishbmc

sreproduction-engineeringinfrastructureautomationlinux

NVIDIA DGX Cloud builds and operates large-scale GPU infrastructure for AI workloads. We are looking for Software Engineers with SRE or Production Engineering experience who have worked hands-on with bare-metal NVIDIA systems. This team builds the software and operational tooling that moves GPU capacity from installed hardware to production service supporting an IaaS production environment of BMaaS, VMaaS.

What makes this opportunity outstanding is the chance to work with innovative technology to develop the future of AI computing. Join us to be part of a world-class team and make an impact on the next era of computing! At NVIDIA, you’ll help make next-generation AI infrastructure production-ready at scale!

What you’ll be doing:

Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management.
Build tools using BMC and Redfish interfaces to assess hardware health, regulate server state, and facilitate recovery workflows.
Manage and enhance NVIDIA NVL72 systems and BlueField-3 or later DPUs within cloud partner and on-premises environments.
Diagnose failures across servers, DPUs, GPU systems, CPU systems, networking, Linux, and Kubernetes; turn recurring issues into automated detection and repair.
Define validation and handoff criteria so new capacity enters production safely and consistently.
Take part in on-call duties, incident response, root-cause analysis, and ensure permanent resolutions are implemented.
Collaborate with hardware, networking, platform, data center operations, and partner teams to resolve issues across ownership boundaries.

What we need to see:

8+ years building software for or operating production infrastructure, including substantial hands-on bare-metal experience.
Strong Go or Python skills, with a record of delivering production automation and services.
Direct experience working with BMC and Redfish for server provisioning, health inspection, power control, or fault diagnosis.
Practical experience working directly with NVIDIA GPU hardware, including NVL72 systems, and BlueField-3 or later DPUs.
Experience with Linux, firmware and driver management, network boot, and the server lifecycle from initial provisioning through repair.
Experience managing production reliability via on-call duties, incident handling, observability, and durable solutions.
Ability to debug failures across hardware, host operating systems, networking, and distributed services.
Clear communication and demonstrated ownership of problems that span multiple teams.
BS/MS in Computer Science or equivalent experience in a related field.

Ways to stand out from the crowd:

Experience operating BlueField DPUs in DPU mode, including host-to-DPU connectivity and lifecycle debugging, or equivalent experience.
Background with NVLink, InfiniBand, Spectrum-X, or GPU cluster performance validation.
Experience building safe, repeatable workflows for rack-scale bringup, firmware upgrades, hardware replacement, and customer handoff.
Background with Kubernetes, GitOps, Argo CD, SLOs, and fleet-wide automation.

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 13, 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.

How we rate this

Software Engineer, SRE and Production Engineering - DGX Cloud at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Software Engineer, SRE and Production Engineering - DGX Cloud is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on October 9, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

SreProduction EngineeringInfrastructureAutomationLinuxGoPythonKubernetes

Questions you could be asked

Tell me about a project where sre was part of your work. What did you do?
Tell me about a project where production engineering was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Tell me about a project where automation was part of your work. What did you do?
Tell me about a project where linux was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Sre, Production Engineering, Infrastructure, Automation, and Linux. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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