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.

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.