
10,000+ employees
Founded 1993
🏥 Healthcare
🏭 Manufacturing
🤖 Artificial Intelligence
Healthcare • Manufacturing • Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
🕒 5 days ago
🏄 California, Colorado, +3 more states – Remote
💵 $184k - $356.5k / year
⏰ Full Time
🟠 Senior
👮♂️ Cybersecurity / Security Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 11%
Where this job comes from
Posted on NVIDIA's careers page, not through a job board
First seen by Remote Rocketship 5 days ago
Still open on NVIDIA's site. Checked 2 hours ago.

10,000+ employees
Founded 1993
🏥 Healthcare
🏭 Manufacturing
🤖 Artificial Intelligence
Healthcare • Manufacturing • Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
• Build leading software to accelerate and improve cybersecurity tooling for AI • Collaborate with research and product teams to develop research code into alpha product versions • Identify high-value MVPs for ambiguous security and identity problems • Prototype solutions, validate them with partner teams, and iterate toward production-ready services • Develop reusable skills, CLI tools, APIs, and integration patterns for secure agent approaches across enterprise tools and platforms • Partner with Enterprise Security, Product Security, Enterprise AI, Enterprise Product, and platform teams • Align architecture with real workflow needs and operational constraints • Build practical solutions and lasting code bases from sophisticated problems and basic prototypes
• Bachelor’s degree or Master’s degree or equivalent experience in Computer Science or a related field • 8+ years in software engineering, security engineering, or related areas, including hands-on technical leadership • Excellent software engineering skills, including crafting and building backend services, APIs, automation, or platform components in various programming environments • Ability to quickly learn new paradigms, frameworks, and tools as needed • Experience with multi-contributor software projects and long-running software projects • Familiarity with building agents, AI tooling, and architectures • Track record of framing problem spaces, defining an MVP, prototyping quickly, and evolving ideas into production systems • Familiarity with offensive security, adversarial thinking, red teaming, or attack-path analysis • Ability to apply offensive-security perspectives to architecture decisions and security tradeoffs • Flexibility and willingness to frequently collaborate across organizational boundaries • Strong human-centered thinking and ability to integrate requirements from researchers and users into code • Ability to build reusable frameworks, understand and refine requirements, and build tooling that improves engineering velocity and consistency • Deep familiarity with open-source projects, including community involvement, workflow, and governance • Experience with agentic or AI-adjacent systems, such as tool-using applications, workflow orchestration, evaluation loops, policy controls, memory/context services, or trust and discovery systems • Understanding of AI-specific security risks such as injection, tool misuse, unauthorized access expansion, data exfiltration, or unsafe delegation patterns
• Equity • Benefits
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