Senior SWQA Test Development Engineer

NVIDIA•Santa Clara, CA

4d•$168,000 - $322,000

About The Position

NVIDIA is seeking a senior, technically strong test development engineer to drive quality, automation, and technical leadership for AI microservices and inference platforms. The role owns end-to-end quality from design through release and production readiness, and helps set quality standards for next-generation AI microservices. The engineer partners with cross-functional teams to influence architecture and improve testability, while providing technical leadership and mentorship to less senior engineers. The position covers test strategy, planning, and execution across functional, integration, system, performance, and reliability testing. It involves building and maintaining automation frameworks for microservice-based, containerized AI systems; validating LLM and AI inference workflows; and driving defect triage, root-cause analysis, and quality metrics. AI-assisted testing techniques are used to improve coverage, efficiency, and the quality of test results. The role offers the opportunity to influence architecture and lead quality efforts alongside NVIDIA engineers. Base salary depends on location, experience, and other objective job-related factors. The stated base salary ranges are $168,000–$270,250 for Level 4 and $200,000–$322,000 for Level 5. The position is also eligible for equity and benefits. Applications will be accepted at least until November 7, 2026. This is an existing vacancy.

Requirements

BS or higher degree in CS, EE, or CE, or equivalent experience.
8+ years of experience in software development, test development, or quality engineering roles.
Strong proficiency in Python and test automation frameworks.
Experience testing distributed systems, microservices, or cloud-native platforms.
Solid understanding of Linux, Docker, Kubernetes, and CI/CD pipelines.
Proven ability to lead technically, review designs, and mentor other engineers.
Strong debugging skills and ability to reason about complex, system-level failures.
Excellent communication skills and experience working across geographically distributed teams.

Nice To Haves

Experience testing AI/ML platforms, LLM pipelines, or inference services.
Hands-on exposure to NeMo, NIM, or model-as-a-service platforms.
Experience with performance, scale, and reliability testing in production-like environments.
Experience applying AI tools to enhance test development, automation, and diagnostics.
Prior ownership of quality for customer-facing or production-critical services.

Responsibilities

Own and drive end-to-end quality from design through release and production readiness.
Lead test strategy, planning, and execution across functional, integration, system, performance, and reliability testing.
Design, build, and maintain test frameworks and automation for microservice-based, containerized AI systems.
Provide technical leadership and mentor less senior engineers on test design, automation practices, and quality standards.
Partner with cross-functional teams to influence architecture and improve testability.
Validate LLM and AI inference workflows, including model lifecycle, APIs, CLIs, deployment configurations, and scaling scenarios.
Drive defect triage, root-cause analysis, and quality metrics to ensure issues are addressed systematically and efficiently.
Use AI-assisted testing techniques to improve coverage, efficiency, and signal-to-noise in test results.