Level

NVIDIA

Senior AI Security Engineer

NVIDIA is hiring a Senior AI Security Engineer in Seattle, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Builds AI ●●●● is how Level rates this cybersecurity role: the job is building AI systems.
  • The listed pay starts 16% above the typical cybersecurity posting on Level.
  • Tools and skills the posting cites include Python, APIs and Cli Tools.
  • Level lists 2,700+ other open roles at NVIDIA.
  • The role was posted in the last few days.

AI in this role

Build secure software, agents, and tooling for AI cybersecurity systems as part of NVIDIA's research team.

pythonapiscli-tools

At NVIDIA, we are stewards of AI. Agents are now a crucial part of cybersecurity where NVIDIA collaborates to set the standard. As model functionality increases and the cybersecurity landscape evolves, we need agents that can seamlessly interface between humans, models, and computing artifacts to build secure environments.


Our Agentic & AI Cybersecurity Research team at NVIDIA is seeking a Senior Engineer. This hands-on role suits someone who transforms sophisticated problems and basic prototypes into practical solutions. They work with research, security, product, and partner teams to build lasting code bases.


What you will be doing:

  • Building leading software ahead of the curve to accelerate and improve cybersecurity tooling for AI.
  • Collaborating closely with research teams and product teams to be responsible for development of research code into alpha versions of products.
  • Rapidly identifying the highest-value MVP for ambiguous security and identity problems, prototyping solutions, validating them with partner teams, and iterating towards production-ready services.
  • Developing reusable skills, CLI tools, APIs, and integration patterns to help internal teams embrace secure agent approaches across enterprise tools and platforms.
  • Partnering closely with teams across Enterprise Security, Product Security, Enterprise AI, Enterprise Product, and relevant platform teams to align architecture with real workflow needs and operational constraints.


What we need to see:

  • 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. The role requires quickly learning 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, capable of applying that perspective to architecture decisions and security tradeoffs.
  • Flexibility and willingness to frequently collaborate across organizational boundaries, balancing security with usability and adoption.

Ways to stand out from the crowd:

  • Demonstrate strong human-centered thinking, carefully integrating underlying requirements from researchers and users into code.
  • Excellent software engineering instincts, including the ability to build reusable frameworks, understand and refine requirements, build tooling that improve 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 24, 2026.

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.

How we rate this

Senior AI Security Engineer at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PythonAPIsCli Tools

Also common in cybersecurity jobs at this level

Pay

This job starts at
$184k
Typical cybersecurity job
$159k

This posting starts 16% above the typical cybersecurity job. See cybersecurity jobs

Questions you could be asked

  1. What's a project where you used Python hands-on?
  2. Walk me through how you've used APIs in your day-to-day work.
  3. What are the limits of Cli Tools that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Python, APIs, and Cli Tools. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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