Senior SWQA Test Development Engineer

NVIDIA • Santa Clara, CA

2d

About The Position

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.

Requirements

• BS or higher degree in CS/EE/CE majors (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
• 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 mentorship to less senior engineers including guiding test design, automation practices, and quality standards
• Partner closely 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, ensuring issues are addressed systematically and efficiently
• Leverage AI‑assisted testing techniques to improve coverage, efficiency, and signal‑to‑noise in test results

Benefits

• You will also be eligible for equity and benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees