Senior AI Infra Test Development Engineer, SDET
Salary not listed • China, Shanghai • Full-time
Posted 12d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a Senior AI Infrastructure Test Development Engineer to join a mission of crafting distributed technology for managing tens of thousands of resources across NVIDIA teams. This role focuses on enabling engineers to concentrate on development and automation by simplifying operational tasks. The engineer will be responsible for creating test plans, execution, and reporting, alongside developing scripts for test automation, designing QA tools, and creating integration tests. The ideal candidate will leverage AI development tools to enhance quality and productivity throughout the QA workflow, including test automation, code generation, and debugging.
Responsibilities
- Architect, implement, and evolve scalable agentic end-to-end SWQA workflows, automated test frameworks, infrastructure, and tooling for complex software products.
- Define test strategy and quality gates across functional, integration, regression, reliability, and release-validation workflows.
- Build and maintain high-value automated coverage for Linux-based, containerized, and Kubernetes environments.
- Investigate and isolate root causes of difficult failures across software stacks, working with development teams for resolution.
- Establish meaningful quality metrics, improve signal-to-noise in test results, and use data to prioritize engineering investment.
- Drive automation efficiency through well-engineered tooling, reusable frameworks, and AI-assisted workflows.
- Raise the technical capability of the wider team through code reviews, design reviews, documentation, and mentorship.
- Take ownership of ambiguous, cross-functional quality problems and deliver durable solutions.
Requirements
- 5+ years of experience in infrastructure software development or test development.
- Strong Python programming skills, with the ability to write clean, maintainable, well-tested code.
- Hands-on experience designing end-to-end SWQA workflows and automation frameworks, including practical use of AI tools to improve test development or debugging.
- Strong Linux expertise and experience testing software deployed with Docker and Kubernetes.
- Solid understanding of risk-based testing, testability, observability, regression strategy, and release criteria.
- Familiarity with bare-metal infrastructure and provisioning or networking technologies (e.g., BMC/Redfish, PXE, DPUs, TCP/IP).
- Ability to debug multi-layer failures spanning services, infrastructure, networking, and deployment configuration.
- Demonstrated technical ownership and communication skills to align stakeholders, deliver solutions, and measure outcomes.
Benefits
- Highly competitive salaries
- Extensive benefits package
- Work environment that promotes diversity, inclusion, and flexibility