NVIDIA's Vulnerability Operations organization is looking for a Security Software Engineer to help operate and improve our AI-powered vulnerability operations platform. This platform uses LLM agents to scan tens of thousands of repositories and live web applications across NVIDIA, then unifies, verifies, and routes those findings to the engineers who can fix them. You'll join a small, fast-moving team and own real production responsibilities from day one — keeping the scanning fleet healthy, improving the triage experience, and making the data trustworthy.
What you'll be doing:
Supporting day-to-day operations of our vulnerability management hub and its two AI scanning engines: monitoring scan fleets and worker queues, investigating stuck or failed scans, and shipping fixes.
Building and maintaining features across the stack — Python/FastAPI backend services, React/TypeScript frontends, and Postgres data models Triaging platform feedback from security engineers and repo owners: reproducing bugs, running data reconciliations in SQL, and closing the loop with users
Operating our GitOps deployment pipeline (Kubernetes/OpenShift, ArgoCD, Vault) — shipping releases to staging and production, rotating secrets, and validating rollouts
Improving scan coverage and data quality: asset inventory across GitLab/GitHub/Gerrit/Perforce, ownership attribution, finding lifecycle and dedup logic
Working alongside senior engineers on the LLM agent harnesses that power scanning and verification, and learning how agentic security tooling is built and operated
What we need to see:
Bachelor's degree in CS/Engineering or equivalent experience
1–3 years of software engineering experience (internships count), with solid Python fundamentals
Working knowledge of SQL and relational databases
Comfort in a Linux/Git environment and a willingness to debug across unfamiliar systems
Interest in security — you don't need to be a security expert yet, but you should want to become one
Strong ownership instincts: you follow problems to root cause and communicate clearly along the way
Ways to stand out from the crowd:
Frontend experience with React and TypeScript
Exposure to containers and orchestration (Docker, Kubernetes, ArgoCD/GitOps) or job-queue/worker architectures (Redis, Celery/ARQ)
Hands-on experience with LLM APIs, agent frameworks, or coding agents (Claude Code, Codex, opencode, or similar)
Security fundamentals: CTF participation, security coursework, bug bounty writeups, or certifications like Security+ or eJPT
Contributions to open-source projects or a portfolio of shipped side projects
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us and, due to unprecedented growth, our elite 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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- 1-3 years of software engineering experience, with internships counting
- Solid Python fundamentals
- Working knowledge of SQL and relational databases
- Comfort working in Linux and Git environments
- Willingness to debug across unfamiliar systems
- Interest in security and willingness to develop security expertise
- Strong ownership instincts and ability to follow problems to root cause
- Clear communication skills
- Frontend experience with React and TypeScript
- Exposure to Docker, Kubernetes, ArgoCD, or GitOps
- Experience with job-queue or worker architectures such as Redis, Celery, or ARQ
- Hands-on experience with LLM APIs, agent frameworks, or coding agents
- Security fundamentals demonstrated through CTFs, coursework, bug bounty writeups, or certifications such as Security+ or eJPT
- Open-source contributions or a portfolio of shipped side projects
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 — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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.”
