VLSI Design Automation Software Engineer

Job Title

VLSI Design Automation Software Engineer

Role Summary

Join a CAD team that builds the infrastructure software for NVIDIA's chip design flows. The team operates compute and storage systems used by physical design engineers worldwide and delivers tools that enable tape-out at scale.

The engineer will design, implement and run production software and AI-driven automation to improve reliability, efficiency and self-service capabilities for VLSI design teams.

Experience Level

Mid-level - 2–6 years of relevant experience building and running production software, ideally in infrastructure, backend services, or developer tools.

Responsibilities

The role owns end-to-end infrastructure software and automation that supports VLSI design teams.

• Architect and implement the software platform for compute infrastructure to provide reliable, efficient, self-service access at scale.
• Build data pipelines, analytics and dashboards to measure usage and performance; use data to inform capacity planning and operational decisions.
• Develop AI agents to diagnose failed jobs, analyze logs, and automate routine engineering tasks.
• Debug job, storage and license issues with physical design engineers (~50% of role) and convert recurring problems into software fixes and self-service tools.
• Own software lifecycle: architecture, storage, UI, testing, CI/CD, deployment and maintenance, including code review and reproducible builds.
• Collaborate across time zones with global teams and mentor junior engineers.

Requirements

Key qualifications and skills. Degrees and formal education are summarized separately below.

Must-have

• Hands-on experience with AI agents or agentic workflows, including LLM APIs, tool calls, or productivity gains from AI assistants.
• 2–6 years building and operating production software (infrastructure, backend services, or developer tools).
• Strong Python skills and solid software engineering fundamentals: design, testing, code review and debugging.
• Strong Linux skills, including shell scripting and debugging across many users and hosts.
• Self-motivated, proactive, able to resolve problems and communicate clearly across sites and time zones under deadline pressure.

Nice-to-have

• Experience with HPC and job schedulers (IBM LSF, Slurm), parallel file systems (NFS), and performance tuning at scale.
• Familiarity with CI/CD (GitLab CI, Jenkins), containers (Docker, Kubernetes), configuration management (Ansible), and monitoring (Prometheus, Grafana).
• Build and source control experience (Bazel, Perforce, Git) and techniques for speeding large builds (remote caching/execution).
• Experience with data modeling, SQL, dashboards and turning data into operational decisions.
• Exposure to C++, Tcl or Perl, and EDA tools or chip design flows (synthesis, place & route, timing analysis).

Education Requirements

B.Sc. or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering or a related field, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.