What if you could create autonomous AI tools that redefine how security works at one of the most innovative companies in the world? The NVIDIA Office of the Chief Security Officer is looking for an AI and Automation Engineer to help us create something new — an AI-native, agent-enabled security organization built from the ground up. As part of the Assurance Engineering team, you’ll partner domain experts who will help you understand the problem space while you bring the engineering skills to solve it. You’ll also collaborate across the broader CSO organization to design and build the agent infrastructure, data pipelines, and MCP integrations that make it all real. If you love building intelligent systems and want to see them make a real impact, this is the role for you.
What you'll be doing:
Allocate dedicated capacity to agent builds — contributing directly to the development of AI agents that support our security programs, including certifications, risk, and compliance.
Build and maintain infrastructure to support agent workflows, including retrieval, context delivery, and agent-to-agent coordination patterns.
Partner with team members to translate business needs into data-driven, agent-ready solutions that reduce manual effort and improve decision velocity.
Architect and implement MCP pattern integrations that enable security agents to interact with data systems, tools, and APIs in a structured, scalable way.
Own the design, deployment, and maintenance of ETL and agentic data pipelines to ingest, transform, and serve data from multiple sources into our data lakehouse and downstream agent consumers.
Ensure data security, privacy, and governance are implemented across all pipelines and agent-accessible data surfaces.
Continuously monitor, optimize, and resolve issues with data infrastructure, pipelines, and agents for efficiency, accuracy, speed, and scalability in support of real-time agent workloads.
Mentor other engineers on data engineering, MCP patterns, and agent-native design principles.
What we need to see:
Bachelor’s or Master’s degree in Computer Science, Engineering, IT, or related field (or equivalent experience).
8+ years of working experience in Automation Engineering and Data Engineering.
Proficiency with Python, Go, C++, or other relevant languages.
Experience working and building production workflows with AI, agents, and MCPs.
Familiarity with Claude Code, Codex, Cursor, or similar tools.
An ability to ramp quickly on the use and implementation of new AI tools and MCP patterns.
Prior experience with AWS, Terraform, Airflow, and Databricks or equivalent large-scale data platforms.
Strong ownership, self-sufficiency, and ability to lead in agile, fast-moving environments.
Proven ability to deliver high-impact, large-scale projects with minimal direction.
Excellent verbal and written communication skills.
Ways to stand out from the crowd:
Direct experience building or supporting AI agent pipelines in a security, compliance, or enterprise operations context.
Familiarity with NVIDIA's AI stack and a genuine passion to build security programs on top of it.
Previous background in Information Security or Cybersecurity.
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 or Master's degree in Computer Science, Engineering, IT, or a related field, or equivalent experience
- 8+ years of experience in Automation Engineering and Data Engineering
- Proficiency with Python, Go, C++, or other relevant programming languages
- Experience building production workflows with AI agents and MCPs
- Familiarity with Claude Code, Codex, Cursor, or similar tools
- Ability to quickly learn and implement new AI tools and MCP patterns
- Experience with AWS, Terraform, Airflow, and Databricks or equivalent large-scale data platforms
- Strong ownership, self-sufficiency, and ability to lead in agile, fast-moving environments
- Ability to deliver high-impact, large-scale projects with minimal direction
- Excellent verbal and written communication skills
- Experience building or supporting AI agent pipelines in security, compliance, or enterprise operations contexts
- Familiarity with NVIDIA's AI stack and interest in building security programs on it
- Previous Information Security or Cybersecurity background
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.”
