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 other objective job-related factors. The expected base salary ranges for this position are:
- 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 November 3, 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.
