Senior AI Infrastructure Engineer - Security and Networking

We're looking for a Senior AI Infrastructure Engineer to join a group that specializes in Security and Networking, and specifically ML/AI, MLOps, and agentic AI development. As a Senior AI Infrastructure Engineer, you’ll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, and security architects to ensure smooth development, deployment, evaluation, and optimization of AI pipelines, models, and agents. This role requires a balance of high-level engineering rigor and a collaborative spirit; you’ll be a technical anchor and a supportive peer for teams across the organization.

What You’ll Be Doing

Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production.

Managing ML/agentic workflows to ensure performance, high availability, resource efficiency, and cost-effectiveness.

Designing and implementing pipelines and frameworks for AI training, inference, and experimentation.

Partnering with data scientists and security architects to operationalize AI agents, including packaging and integration with existing systems. This includes contributing to and reviewing code, design documents, and test plans.

Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes, ensuring reliable deployments and rollbacks.

Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production.

Implementing access controls, authentication mechanisms, and encryption standards to keep our AI models and data secure.

Documenting guidelines and leading knowledge-sharing sessions to elevate the team’s collective development expertise.

What We Need To See

BSc/MSc in CS/CE or related field (or equivalent experience)

At least 8 years of experience in ML engineering with a track record of deploying LLMs and agents to production at scale (including distributed environments).

Proficiency in Python and/or C++, with a deep understanding of ML/AI frameworks.

Hands-on experience with microservices, container orchestration, and cloud platforms for large-scale training and inference workloads.

Knowledge of ML training and inference optimization techniques.

Understanding of build infrastructure and CI/CD tools and practices (e.g. GitLab, GitHub Actions, Jenkins)

Experience with teaching and mentoring.

You are a proactive owner who takes pride in your work but remains humble and approachable. You believe that "how" we build is just as important as "what" we build.

Excellent collaboration skills, with the ability to explain complex infra concepts to non-technical stakeholders clearly and kindly.

Ways to stand out from the crowd

Experience deploying and optimizing generative models and multi-agent systems for performance.

Deep systems knowledge (Linux internals, network protocols, or high-performance computing).

A background in security research, including knowledge of firewalls, intrusion detection, or network architectures.

NVIDIA has some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. We are committed to fostering a diverse 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.

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