Level

NVIDIA

Engineering Manager, Agentic AI

AI in this role

Lead a software engineering team building foundational core libraries and scalable tooling for autonomous agentic AI applications.

pytorchgpuvector-databasesrag-systems
ragai-agentsartificial-intelligenceagentic-systemssoftware-engineeringteam-managementgpu-optimization

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.


We are looking for an experienced Software Engineering Manager to lead the development of our core libraries for Agentic Applications. Are you excited by the prospect of building a team working on foundational, brand-new technology that powers the next generation of autonomous systems? Have you ever dreamed of elevating engineering practices to enable the safe and scalable deployment of agentic systems? As a global leader in AI and deep learning, NVIDIA is redefining industries and our work in agentic computing is at the forefront of this revolution. Join us in building the scalable agentic capabilities, reusable building blocks, and high-quality libraries that will accelerate developer productivity, ensure agent quality, and provide critical acceleration and optimization for highly performant and efficient agents. Work directly with a community of creative engineers and collaborate on projects that push the boundaries of what's possible in the world of autonomous agents!


What you'll be doing:

  • Track and understand evolving agent development patterns across NVIDIA and the broader ecosystem, maintaining current knowledge of both research and commercial products.
  • Lead a team which identifies gaps and friction in current agent architectures, and translate insights into agentic tools that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops.
  • Providing technical guidance and mentorship to team members, encouraging a collaborative and inclusive environment.
  • Coordinating the entire development lifecycle, from ideation to deployment, ensuring flawless execution.
  • Integrate high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows to deliver best-in-class, high-performance agentic applications.
  • Partnering with product management and other collaborators to determine project requirements and priorities.
  • Lead and grow a high-performing team along with a multi-functional community to standardize procedures and scale adoption of our agent libraries.

What we need to see:

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Applied Math, or a related field, or equivalent experience.
  • A minimum of 7 overall years of experience, including 3+ years in team management, with strong interpersonal and leadership skills.
  • Proven track record in designing and deploying modern agent architectures and open-source frameworks, with a history of translating proof-of-concept initiatives into production-grade solutions driving measurable impact.
  • Demonstrated strategic vision to translate the rapidly evolving AI domain into platform roadmaps and high-value technical outcomes.
  • Exceptional communication and cross-functional leadership skills, with proven success collaborating with and contributing to the open-source community.

Ways to stand out from the crowd:

  • Experience building evaluation/benchmarking systems for agent workflows (metrics, regression, feedback loops).
  • Led a team that delivered reliable and scalable enterprise-grade agents deployed to customers or across an organization.
  • Experience implementing enterprise-grade governance for agent systems (observability, monitoring, policy enforcement) in production autonomous workflows.
  • Developed tools used by multiple teams to accelerate deployment of agents (SDKs, templates, reference apps, reusable building blocks).
  • Proven track record of maintaining, creating, or leading major open-source libraries or developer tools.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 2, 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

Engineering Manager, Agentic AI at NVIDIA rates 90 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. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI AgentsArtificial IntelligenceAgentic SystemsSoftware EngineeringTeam ManagementGPU OptimizationPyTorch

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Tell me about a project where artificial intelligence was part of your work. What did you do?
  4. Tell me about a project where agentic systems was part of your work. What did you do?
  5. Tell me about a project where software engineering was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Agents, Artificial Intelligence, Agentic Systems, and Software Engineering. 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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