AI Automation Engineer, Security

NVIDIA•Austin, TX

About The Position

The NVIDIA Office of the Chief Security Officer is looking for an AI and Automation Engineer to help create an AI-native, agent-enabled security organization. As part of the Assurance Engineering team, you will partner with domain experts to understand the problem space and apply engineering skills to solve it. You will also collaborate across the broader CSO organization to design and build the agent infrastructure, data pipelines, and MCP integrations necessary for this new security model.

Requirements

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.

Nice To Haves

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.

Responsibilities

Allocate dedicated capacity to agent builds — contributing directly to the development of AI agents that support 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.