Senior Software Engineer, SRE and Production Engineering - DGX Cloud
NVIDIA is hiring a Senior Software Engineer, SRE and Production Engineering - DGX Cloud for a remote role open to applicants in Canada. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions Kubernetes, Python and Go among its tools and skills.
- NVIDIA has 2,700+ other open roles on Level.
- Posted within the past week.
AI in this role
Build and operate large-scale GPU infrastructure and automation for AI workloads on NVIDIA DGX Cloud.
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 you’ll be doing:
- Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management.
- Develop tools that interact with BMC and Redfish interfaces to monitor hardware health, manage server state, and assist recovery workflows.
- Handle and advance NVIDIA NVL72 systems and BlueField-3 or later DPUs throughout 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 follow-up to implement permanent solutions.
- Work with hardware, networking, platform, data center operations, and partner teams to resolve issues across ownership boundaries.
What we need to see:
- 12+ 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 with BMC and Redfish in server provisioning, health inspection, power management, or fault diagnosis.
- Practical experience working directly with NVIDIA GPU hardware, such as NVL72 systems, and BlueField-3 or newer DPUs.
- Experience with Linux, firmware and driver management, network boot, and the server lifecycle from initial provisioning through repair.
- Experience managing production reliability through on-call duties, incident response, 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 practical setting.
Ways to stand out from the crowd:
- Experience operating BlueField DPUs in DPU mode, including host-to-DPU connectivity and lifecycle debugging, with DPU or equivalent experience considered.
- 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.
- Experience with Kubernetes, GitOps, Argo CD, SLOs, and fleet-wide automation.
At NVIDIA, you’ll help make next-generation AI infrastructure production-ready at scale!
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 6, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
How we rate this
Senior Software Engineer, SRE and Production Engineering - DGX Cloud at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
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 infrastructure was part of your work. What did you do?
- Tell me about a project where hardware provisioning was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Walk me through how you've used Kubernetes in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Sre, Infrastructure, Hardware Provisioning, Distributed Systems, and Kubernetes. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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