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AI Automation Engineer, Security
NVIDIAAI Automation Engineer developing intelligent AI-native security tools and infrastructure at NVIDIA. Collaborating with experts to enhance security programs through automation and data engineering.
Posted 6/12/2026full-timeRemote • California, Texas • 🇺🇸 United StatesSeniorLead💰 $168,000 - $310,500 per yearWebsite
Tech Stack
Tools & technologiesAirflowAWSETLGoPythonTerraform
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- Equity
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Hard Skills & Tools
PythonGoC++Automation EngineeringData EngineeringETLMCP patternsdata pipelinesdata securitydata governance
Soft Skills
ownershipself-sufficiencyleadershipagile methodologycommunication