VLSI Design Automation Software Engineer

We're seeking a dedicated and driven Software Engineer to join our dynamic team at NVIDIA, responsible for managing and maintaining high-quality VLSI development infrastructure for the Backend Networking team.

As a VLSI Design Automation Software Engineer, you will oversee and optimize compute and storage resources, ensuring operational efficiency and success of VLSI projects. You will develop and maintain scripts, automation tools, and AI-assisted workflows to streamline infrastructure tasks and improve developer productivity.

Responsibilities:

• Oversee and optimize compute and storage resources, ensuring operational efficiency and success of VLSI projects.
• Develop and maintain scripts, automation tools, and AI-assisted workflows to streamline infrastructure tasks and improve developer productivity.
• Design, implement, and maintain dashboards for monitoring and reporting on infrastructure performance and usage.
• Work closely with a remote team in Israel, ensuring smooth communication and coordination on infrastructure-related tasks.
• Engage in the entire lifecycle of infrastructure tool development, including design, testing, deployment, and maintenance.
• Collaborate with other team members and DA teams to implement innovative software solutions and agentic coding practices using modern AI tools.

Requirements:

• Bachelor's degree in computer science/engineering or equivalent experience.
• Minimum 3 years' experience with VLSI Design Automation.
• Strong proficiency with Unix.
• Proven experience in at least two programming languages, including Python, and scripting.
• Experience working with AI coding assistants, agentic development workflows, or productivity-enhancing automation tools.
• Good debugging and problem-solving skills.
• Strong interpersonal skills along with the ability to work in a diverse team.

Preferred Qualifications:

• Background with SQL and LSF scheduler.
• Experience with GUI and Unix/web application development.
• Familiarity with programming languages such as React and Python.
• Hands-on experience with AI tools such as Cursor and Claude Code.
• Experience building internal coding agents, or integrating AI into engineering workflows.