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NVIDIA

Software DevOps Engineer, Networking

Posted 5 Hours Ago
Be an Early Applicant
In-Office
Santa Clara, CA, USA
148K-276K Annually
Senior level
In-Office
Santa Clara, CA, USA
148K-276K Annually
Senior level
Owns end-to-end CI/CD, build, test, security, and release infrastructure for NVIDIA networking software. Responsibilities include maintaining GitLab CI, Jenkins, and GitHub Actions pipelines; operating Kubernetes-based build fleets, registries, and artifact repositories; automating hardware and simulation environments with Python, Bash, and Ansible; integrating quality and security gates; stabilizing regression pipelines; and partnering with engineering teams on release processes and repository standards.
The summary above was generated by AI

NVIDIA's networking software runs the fabrics inside the world's largest AI systems: NVLink and InfiniBand switch management, subnet managers, in-network computing, and fabric telemetry. Our infrastructure and DevOps team owns how that software is built, tested, scanned, and released — the CI/CD pipelines, Kubernetes-based build fleets, artifact and container registries, quality and security gates, and the hardware-simulation and lab environments the product teams rely on every day. We are looking for a senior DevOps engineer who is at home on Linux, automates in Python and Bash without hesitation, and takes pipelines end to end, from a red nightly to a signed release. The work spans a dozen active repositories and three CI systems, together with a distributed team of DevOps and product engineers across the US and Israel. Every build the networking software organization ships passes through what this role owns.

What you'll be doing:

  • Design, build, and maintain CI/CD pipelines for a portfolio of networking software products across GitLab CI, Jenkins, and GitHub Actions — from merge-request gates to nightly regressions and release pipelines that package, sign, and publish Debian and RPM packages and container images.

  • Keep pipeline signal trustworthy: make failures visible and actionable, remove failure masking, stabilize flaky lanes, and turn nightly regression results into something product teams act on.

  • Operate and evolve the build infrastructure — Kubernetes-based CI runner fleets, container registries and artifact repositories, caching, retention policies, and access control.

  • Integrate quality and security gates into every pipeline: code coverage, static analysis, unit and functional test lanes, secret and container scanning, dependency and vulnerability scanning — and drive findings to closure with the owning teams.

  • Automate provisioning of hardware- and simulation-based test environments with Ansible and Python.

  • Partner with C++ and Python developers, verification engineers, and lab and infrastructure teams to unblock builds, harden release paths, and set repository standards — branch protection, code owners, merge policies.

  • Apply AI-assisted tooling to DevOps work — automated code review, failure-triage assistants, agent workflows — wherever it removes toil.

What we need to see:

  • Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.

  • 5+ years in DevOps, build and release, or infrastructure engineering roles, including pipelines owned end to end.

  • Deep, hands-on Linux skills on Ubuntu and RHEL: shell fluency, process and system debugging, package management, operating fleets of hosts, and containers with Docker.

  • Strong automation in Python and Bash.

  • Production track record with at least one modern CI system — GitLab CI, Jenkins pipelines, or GitHub Actions — including multi-stage pipelines for both compiled and interpreted codebases.

  • Working knowledge of Kubernetes as a CI and infrastructure platform, plus container registries and artifact repositories.

  • Familiarity with software quality and security tooling: coverage, static analysis, secret and vulnerability scanning.

  • Solid grounding in computer networking fundamentals and Git-based development workflows.

  • Ownership and clear communication — able to drive a problem across teams and time zones and to document what you build.

Ways to stand out from the crowd:

  • Building and packaging C/C++ projects with CMake and Conan, and keeping large compiled builds fast and reproducible.

  • Familiarity with high-performance networking — InfiniBand, Ethernet fabrics, NVLink — or with switch and network-management software.

  • Running SonarQube, Coverity, Bullseye, or container and secret scanning at scale.

  • Practical use of AI agents and LLM tooling to automate DevOps and verification workflows.

  • Excellent interpersonal and communication skills

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, 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 148,000 USD - 235,750 USD for Level 3, and 176,000 USD - 276,000 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 20, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

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