What does it take to establish a team that reshapes how software quality works by building autonomous systems that think, triage, and act? We are looking for a hands-on engineering leader who is deeply technical and driven to create an environment where a small team of exceptional engineers can do their best work. The right person for this role is obsessed with building things, spends evenings experimenting with AI coding tools and agent frameworks as a hobby, and brings that energy to every problem at work. If you love turning ambiguous, high-stakes technical challenges into shipped systems — and you believe excellent management means clearing the path for builders — this role was made for you. What you’ll be doing: Building and leading a team of test and tools development engineers who design agentic test pipelines, quality infrastructure, and autonomous workflows for Omniverse Owning the technical vision for AI-powered quality infrastructure — multi-agent orchestration for test generation, failure triage, root cause analysis, and automated bug filing Setting speed-of-light goals that compel the team to rethink assumptions, not just work harder — and making architecture decisions that balance ambition with production reliability Establishing evaluation frameworks for AI-generated outputs, ensuring autonomous pipelines are reliable and observable — not just fast Partnering with QA leadership, platform teams, and product engineering to identify high-leverage automation opportunities and ensure the tools this team builds are trusted and adopted Attracting, coaching, and retaining top engineering talent — fostering a culture of ownership, intellectual honesty, and relentless experimentation where engineers feel safe to take bold bets What we need to see: Bachelor’s degree in Computer Science, or a related field 8+ overall years of software development or software test development experience 3+ years of engineering management or technical leadership experience, including hiring, coaching, and growing senior engineers Strong Python engineering skills with the ability to review code, prototype solutions, and make credible architecture decisions Hands-on experience building or leading teams that shipped multi-agent, autonomous, or AI-powered systems in production Familiarity with AI-native development workflows — large language model APIs, prompt engineering, and AI coding tools used in production contexts Background in test automation, continuous integration and delivery pipeline design, or software quality engineering at scale Track record of translating ambiguous organizational goals into clear technical direction and executable plans Ways to stand out from the crowd: Active experimentation with AI agent frameworks, model context protocol servers, agent skills as a personal hobby or side project — not just at work Deep understanding of where large language models fail—hallucinations, context degradation, and tool misuse—and practical experience building mitigations into production systems Experience crafting evaluation and benchmarking frameworks specifically for AI-generated artifacts Prior work on developer platforms or tools teams where adoption and developer experience were primary success metrics NVIDIA is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. 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/