Software Engineer, SRE and Production Engineering - DGX Cloud
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-10-09). Last seen at its source 1h ago.
We have tracked this listing since 10 Oct 2026 (1 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$184k–287.5k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workday employer's own board first seen 1d ago · last seen 1h ago
- location not stated
The listing
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.
You will also be eligible for equity and benefits.
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.