Senior AI Agent Test Developer, SDET

NVIDIA•Santa Clara, CA

About The Position

NVIDIA is seeking a senior test development engineer to drive quality, automation, and technical leadership for AI agents and end-to-end agentic workflows on NVIDIA GPU platforms. The role develops test plans and strategies to validate how models, agent harnesses, tools, and inference runtimes work together, and builds agentic quality-assurance solutions to improve test development, execution, and failure analysis. The position uses and develops AI-powered tools to make software testing more effective, including improving test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. It works with product, engineering, and cross-functional teams to review requirements, define test strategies, build and execute test plans, report quality status and risks, and verify fixes. Testing includes functional, performance, fault-injection, reliability, and regression testing for AI applications, agents, and end-to-end workflows. The role also automates test cases and contributes to scalable test frameworks and agent test harnesses.

Requirements

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 and problem-solving skills, and curiosity for complex technology.

Nice To Haves

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.

Responsibilities

Use and develop AI-powered tools to improve software testing.
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 applications, 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.