System Software Engineer – Security Tools and Infrastructure

NVIDIA•Santa Clara, CA

About The Position

NVIDIA is seeking a highly motivated system software engineer with a strong bias toward security tooling, infrastructure, and quality to join the GPU Software team. In this role, you will design and build automation frameworks and services that enable secure GPU firmware development at scale—spanning fuzzing infrastructure, signing and chain-of-trust workflows, key management and derivation (including HSM integration), and regression testing automation. You'll partner closely with software engineers worldwide to maintain and scale our fuzzing infrastructure platform, deploy reliable security services and automation on modern infrastructure platforms (CI/CD, Kubernetes, and cloud environments), and promote AI technologies to improve developer experience and productivity across the GPU security toolchain. What you'll be doing: Maintain and scale fuzzing infrastructure, onboarding new fuzzers, optimizing coverage and performance, and collaborating cross-functionally with security, QA, and product teams to integrate fuzzing into development workflows. Design, develop, and integrate security infrastructure for GPU firmware signing, key management and derivation services, incorporating HSMs and collaborating with hardware and software engineers around the world. Evangelize and implement AI powered technologies and workflows to enhance developer experience, productivity, and code quality; exploring opportunities for AI assisted testing, code generation, and intelligent automation. Develop and automate regression testing platforms and tools to improve productivity, reliability, and coverage across GPU security components and workflows. Design, build, deploy, and monitor security automation frameworks and services (e.g., signing, key management, fuzzing automation), integrating with CI/CD pipelines and Kubernetes-based infrastructure. Build out design verification, simulation, quality, and developer workflow capabilities for the GPU Systems Software teams. What we need to see: BS or MS degree in Computer Engineering, Computer Science, or related degree (or equivalent experience). 3+ years of relevant software tooling and infrastructure experience, especially with security or testing focus. Demonstrated hands-on technical background; strong scripting skills (Shell, Python) for automation, diagnostics, and workflow integration. Working knowledge of designing, deploying, operating, and maintaining CI/CD pipelines and jobs (e.g., build, test, signing, fuzzing, release promotion), including troubleshooting and reliability improvements. Relevant experience with tooling and infrastructure technologies like Docker, Kubernetes, Ansible, Jenkins, GitLab CI, Artifactory, SQL/NoSQL databases. Experience with at least one of: fuzzing technologies, cryptography, key management, firmware development, or embedded security. Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.). Ways to stand out from the crowd: Hands-on experience with fuzzing frameworks and tools (AFL, libFuzzer, Syzkaller, or similar) and corpus management strategies. Experience integrating AI/ML technologies into developer workflows or productivity tools. Hands on experience with C, C++, Python, Rust Familiarity with cryptography, security policies, chain of trust, key laddering, and HSMs. Experience with test automation frameworks, regression testing platforms, and continuous testing practices. 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 on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until January 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. 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. NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Requirements

BS or MS degree in Computer Engineering, Computer Science, or related degree (or equivalent experience).
3+ years of relevant software tooling and infrastructure experience, especially with security or testing focus.
Demonstrated hands-on technical background; strong scripting skills (Shell, Python) for automation, diagnostics, and workflow integration.
Working knowledge of designing, deploying, operating, and maintaining CI/CD pipelines and jobs (e.g., build, test, signing, fuzzing, release promotion), including troubleshooting and reliability improvements.
Relevant experience with tooling and infrastructure technologies like Docker, Kubernetes, Ansible, Jenkins, GitLab CI, Artifactory, SQL/NoSQL databases.
Experience with at least one of: fuzzing technologies, cryptography, key management, firmware development, or embedded security.
Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.).

Nice To Haves

Hands-on experience with fuzzing frameworks and tools (AFL, libFuzzer, Syzkaller, or similar) and corpus management strategies.
Experience integrating AI/ML technologies into developer workflows or productivity tools.
Hands on experience with C, C++, Python, Rust
Familiarity with cryptography, security policies, chain of trust, key laddering, and HSMs.
Experience with test automation frameworks, regression testing platforms, and continuous testing practices.

Responsibilities

Maintain and scale fuzzing infrastructure, onboarding new fuzzers, optimizing coverage and performance, and collaborating cross-functionally with security, QA, and product teams to integrate fuzzing into development workflows.
Design, develop, and integrate security infrastructure for GPU firmware signing, key management and derivation services, incorporating HSMs and collaborating with hardware and software engineers around the world.
Evangelize and implement AI powered technologies and workflows to enhance developer experience, productivity, and code quality; exploring opportunities for AI assisted testing, code generation, and intelligent automation.
Develop and automate regression testing platforms and tools to improve productivity, reliability, and coverage across GPU security components and workflows.
Design, build, deploy, and monitor security automation frameworks and services (e.g., signing, key management, fuzzing automation), integrating with CI/CD pipelines and Kubernetes-based infrastructure.
Build out design verification, simulation, quality, and developer workflow capabilities for the GPU Systems Software teams.