Staff Engineer, GPU Front-End Infrastructure/ Methodology
$151,000–$226,600 year
On-site · Austin, Texas, United States
Job Summary
Staff GPU Front-End Implementation Methodology Engineer to shape and advance front-end RTL implementation methodologies for GPU and SoC designs, partnering with architecture, verification, CAD, and physical design teams to uphold best practices and quality standards; own and evolve the RTL flow and build system (including agentic AI workflow support) and contribute to RTL CI/CD, metrics, web applications, and open-source tooling; drive scalable front-end methodologies, remove friction for design and DV teams, lead moderate-to-complex projects, and collaborate across global teams while leveraging RTL concepts and testbench experience.
Required Qualifications
- 6+ years experience with a Bachelor's Degree in Computer Science/Engineering, or 4+ years with a Master’s Degree, or 2+ years with a Ph.D.
- Hands-on experience designing and building agentic AI tools and workflows
- Proficiency across Unix/Linux programming languages including Python, C++, Perl, Ruby, Go, and shell scripting
- Deep Linux system expertise and debugging complex system-level issues
- Solid DevOps, build automation, and build systems experience (GNU Make)
- Experience with containerized environments and orchestration platforms (Docker, Kubernetes, OpenShift)
- Strong analytical and problem-solving skills
- Excellent written and verbal communication skills with technical documentation experience
- Familiarity with RTL design concepts and testbench environments is a plus
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