Run:ai, now part of NVIDIA, is looking for a Senior Software Engineer to build the tools that help engineers develop, validate, and contribute software with confidence. As we expand our open-source ecosystem and adopt agentic development, you’ll shape how contributions are tested and integrated, improve feedback for developers, and help protect NVIDIA’s codebase and internal assets. You’ll work across developer tooling, compatibility validation, scale testing, and AI-assisted contribution workflows, building infrastructure that supports both our engineering teams and the wider open-source community.
What you’ll be doing:
- Build developer tools and CI workflows that simplify development, testing, and contribution for internal engineers and open-source contributors.
- Develop compatibility validation infrastructure that verifies Run:ai across supported software versions and environments.
- Build scale-testing and performance-regression infrastructure that produces repeatable results and actionable diagnostics.
- Develop workflows for agentic PRs, including automated evaluation, testing, and controls that support effective human review.
- Partner with engineering, DevOps, and security teams to enable external contributions while protecting credentials, internal systems, and code integrity.
- Own projects from technical design through rollout, measuring their impact on developer productivity and software reliability.
What we need to see:
- A degree in computer science or a related field, or equivalent practical experience.
- 5+ years of software engineering experience, including building developer tools, shared libraries, or engineering infrastructure.
- Strong programming skills and the ability to design maintainable software used by other engineers.
- Practical experience developing CI/CD pipelines, automated testing frameworks, and Git-based development workflows.
- Ability to diagnose unreliable tests, slow feedback cycles, and recurring development friction, and address their underlying causes.
- Experience delivering and maintaining reliable software, including testing, debugging, and operational support.
- Ability to use AI development tools effectively and evaluate generated code for correctness, security, and maintainability.
- Clear communication, sound engineering judgment, and the ability to collaborate across team boundaries.
Ways to stand out from the crowd:
- Experience maintaining open-source projects or improving external contributor workflows.
- Experience building tooling for coding agents, evaluating AI-generated changes, or automating code review.
- Background with compatibility matrices, performance benchmarking, or scale-testing frameworks.
- Familiarity with secure CI practices, dependency integrity, and running tests on untrusted contributions.
- A track record of measurably improving developer productivity and software reliability.
NVIDIA is 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. If you're creative and autonomous, we want to hear from you!
NVIDIA is committed to fostering a diverse 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.
Skills Required
- Bachelor's degree in computer science or a related field, or equivalent practical experience
- 5+ years of software engineering experience
- Experience building developer tools, shared libraries, or engineering infrastructure
- Strong programming skills and ability to design maintainable software used by other engineers
- Experience developing CI/CD pipelines, automated testing frameworks, and Git-based development workflows
- Ability to diagnose unreliable tests, slow feedback cycles, and recurring development friction
- Experience delivering and maintaining reliable software, including testing, debugging, and operational support
- Ability to use AI development tools and evaluate generated code for correctness, security, and maintainability
- Clear communication, sound engineering judgment, and cross-functional collaboration skills
- Experience maintaining open-source projects or improving external contributor workflows
- Experience building tooling for coding agents, evaluating AI-generated changes, or automating code review
- Experience with compatibility matrices, performance benchmarking, or scale-testing frameworks
- Familiarity with secure CI practices, dependency integrity, and testing untrusted contributions
- Track record of measurably improving developer productivity and software reliability
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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