Senior Software Engineer, Infrastructure Development

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Engineer role focused on developing infrastructure software and manufacturing test solutions for Datacenter and Enterprise products. The role involves building scalable internal tools, modern web-based platforms, and AI-enhanced workflows to improve engineering productivity, diagnostic development, test automation, and manufacturing operations. Key responsibilities include developing AI-assisted tools and workflows using LLMs, RAG, agents, and function calling to upgrade internal platforms and tools.

What you'd actually do

  1. 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.
  2. Build universal frameworks to standardize diagnostic structures, workflows, metadata, and release processes across NVIDIA products.
  3. Develop and maintain diagnostic management systems to handle, optimize, and automate the release process for NVIDIA board and system products.
  4. 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.
  5. 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.

Skills

Required

  • BS in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience, with 5+ years of software development experience
  • Strong understanding of full-stack application development
  • Excellent Python programming skills
  • bash scripting experience
  • Solid experience with database design
  • Familiarity with JavaScript, React, CSS, and HTML
  • Experience with yarn or npm is required
  • Familiarity with authentication and security concepts
  • Familiarity with best software development practices
  • Hands-on experience using AI tools to improve software development productivity
  • Practical understanding of AI application development concepts

Nice to have

  • TypeScript
  • Create React App
  • Webpack
  • modern frontend build systems
  • 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

What the JD emphasized

  • Hands-on experience using AI tools to improve software development productivity
  • 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.

Other signals

  • AI-enhanced workflows
  • AI-assisted tools
  • LLMs, RAG, agents, function calling