Senior Software Engineer, Infrastructure Development

NVIDIA•Santa Clara, CA

3d•$132,000 - $253,000

About The Position

We are looking to hire a Senior Software Engineer to join the Test Solutions Group at NVIDIA, developing infrastructure software and manufacturing test solutions for Datacenter and Enterprise products. In this role, you will collaborate closely with hardware design, test engineering, product engineering, and software teams to enable NVIDIA’s next-generation GPU and CPU-based server products. This role is ideal for someone who is passionate about building scalable internal tools, modern web-based platforms, and AI-enhanced workflows that improve engineering productivity, diagnostic development, test automation, and manufacturing operations. NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a learning machine that constantly evolves by adapting to new opportunities that are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work: to amplify human creativity and intelligence. Make the choice to join our growing team today.

Requirements

BS in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience, with 5+ years of related software development experience.
Strong understanding of full-stack application development, including frontend, backend, database, deployment, and system integration.
Excellent Python programming skills and bash scripting experience.
Solid experience with database design, including crafting schemas from scratch, writing efficient queries, understanding execution plans, and applying indexes effectively.
Familiarity with JavaScript, React, CSS, and HTML.
Experience with yarn or npm is required.
Familiarity with authentication and security concepts, including NTLM, OAuth, JWT, role-based access control, and secure API design.
Familiarity with best software development practices, including documentation, testing, code review, CI/CD, containerization, and reliable production deployment.
Hands-on experience using AI tools to improve software development productivity, such as coding assistants, AI-based debugging, documentation generation, test generation, or workflow automation.
Practical understanding of AI application development concepts, such as LLM APIs, prompt engineering, retrieval-augmented generation, vector databases, AI agents, tool/function calling, and model evaluation.
Passion for using AI to modernize engineering workflows, automate repetitive processes, improve internal tools, and unlock new productivity for cross-functional teams.

Nice To Haves

TypeScript, Create React App, Webpack, or modern frontend build systems are strong pluses.
Experience building AI-powered internal tools, developer productivity platforms, chatbots, agents, or automation systems.
Experience working with manufacturing test, hardware diagnostics, lab automation, product validation, or large-scale engineering operations.
Experience integrating enterprise data sources, internal APIs, documentation systems, logs, or test databases into AI-assisted workflows.
Experience with containerized services, Kubernetes, Docker, GitLab CI/CD, or cloud/on-prem infrastructure.

Responsibilities

Develop industry-standard three-tier web-based IDEs and platforms to automate and intelligentize diagnostic creation, verification, validation, and release for NVIDIA system-level products, including GeForce, Quadro, HGX, and DGX.
Build universal frameworks to standardize diagnostic structures, workflows, metadata, and release processes across NVIDIA products.
Develop and maintain diagnostic management systems to handle, optimize, and automate the release process for NVIDIA board and system products.
Design and implement AI-assisted tools and workflows to improve engineering productivity, including AI-powered search, code generation, documentation assistance, log analysis, test result summarization, workflow automation, and intelligent troubleshooting.
Apply modern AI technologies, including LLMs, RAG, agents, function calling, semantic search, and workflow orchestration, to upgrade TSG’s infrastructure platforms and internal engineering tools.
Work closely with Test Development Engineering, Product Development Engineering, Software Engineering, and Operations teams to solve sophisticated infrastructure, security, automation, and development challenges.
Explore and evaluate new AI tools, frameworks, and development practices, and apply them pragmatically to improve software delivery, test infrastructure, and manufacturing support workflows.