Senior AI Agent Test Developer, SDET

NVIDIA is the world leader in accelerated computing and AI. Our technologies power the most advanced AI platforms, including NeMo microservices and NVIDIA Inference Microservices (NIM), enabling scalable, production‑grade AI deployment across cloud and enterprise environments. We are looking for a senior, technically strong test development engineer to drive quality, automation, and technical leadership in this rapidly evolving space.

We are looking for a Senior AI Agent Test Developer to help deliver reliable AI agents and end-to-end agentic workflows on NVIDIA GPU platforms. You will develop test plans and strategies to validate how models, agent harnesses, tools, and inference runtimes work together. You will also build agentic QA solutions that improve test development, execution, and failure analysis.

• →Use and develop AI-powered tools to make software testing smarter, faster, and more effective!
• →Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization.
• →Work with product, engineering, and cross-functional teams to review requirements and define test strategies.
• →Build test plans, design and execute test cases, and report quality status, risks, bugs, and results.
• →Perform functional, performance, fault-injection, reliability, and regression testing for AI apps and agents and end-to-end agentic workflows.
• →Automate test cases and contribute to scalable test frameworks and agent test harnesses.
• →Manage the bug lifecycle, reproduce customer issues, and verify fixes.

• MS or PhD in Computer Science, Engineering, or a related field (or equivalent experience).
• 8+ years of QA, test automation, or software testing experience.
• Hands-on experience developing, testing, and maintaining AI agents or their underlying components, such as models, agent harnesses, and inference runtimes.
• Practical experience configuring, running, and debugging open-source models using at least one inference runtime or framework.
• Strong QA fundamentals, test strategy, test planning, and failure analysis skills.
• Proficiency with Unix/Linux, Python programming, and shell scripting.
• Experience with Kubernetes, containers, CI/CD pipelines, and cloud-native systems.
• Experience testing observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or similar platforms.
• Experience with large-scale failure testing, using tools such as KWOK, Chaos Monkey, or similar frameworks.
• Strong communication, problem-solving skills, and curiosity for complex technology

• Used AI to reduce testing time, improve defect detection, or increase test coverage.
• Built AI-driven solutions that streamlined QA workflows or reduced manual effort.
• Experience with NVIDIA GPU hardware or GPU-accelerated software.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.