Staff Engineer, GPU Front-End Infrastructure – Methodology

Jobtailor; California (MO); On-site; USD 140,000 - 200,000; Full time

Job summary

Jobtailor is hiring a Senior Front-End RTL Engineer to shape front-end RTL methodologies for GPU/SoC designs. You will enable design and verification teams, collaborate with architecture and CAD groups, and evolve the RTL flow with agentic AI workflow support.

You will own the RTL build system, contribute to CI/CD, metrics, and open-source tooling, and help teams remove friction in front-end workflows while maintaining performance and power objectives.

Qualifications

• 6+ years of experience with a Bachelor’s Degree in Computer Science/Engineering, or 4+ years with a Master’s, 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, including debugging complex system-level issues
• Strong DevOps, build automation, and build-system knowledge (GNU Make)
• Experience with containerized environments and orchestration platforms (Docker, Kubernetes, OpenShift)
• Strong analytical and problem-solving skills with a methodical debugging approach
• Excellent written and verbal communication, with ability to document designs and methodologies
• Proven ability to collaborate across global, cross-functional teams in fast-paced environments
• Familiarity with RTL concepts and testbenches is a plus

Responsibilities

• Shape and advance front-end RTL implementation methodologies for GPU and SoC designs
• Serve as a key enabler for design and verification teams to work faster and at scale
• Partner with architecture, verification, CAD, and physical design groups to define best practices and quality standards
• Own and evolve the RTL flow and build system, including agentic AI workflow support
• Contribute to RTL CI/CD system, metrics collection, and open-source tooling
• Empower design and DV teams by removing friction from front-end workflows
• Drive scalable frontend RTL implementation aligned with performance and power goals
• Take ownership of moderate-to-complex projects and stay ahead of industry trends

Skills

Agentic AI tools development

Unix/Linux programming

Cross-functional collaboration

Problem solving

Education

Bachelor’s Degree in CS/Engineering

Master’s Degree

Ph.D.

Tools

Python

C++

Perl

Ruby

Go

Shell scripting

Docker

Kubernetes

OpenShift

Job description

• Shape and advance the front-end implementation methodologies that underpin high-quality, scalable RTL across complex GPU and SoC designs


• Serve as a key enabler for design and verification teams — helping them work faster, with greater confidence, and at scale


• Partner closely with architecture, verification, CAD, and physical design groups to define and uphold best practices, design guidelines, and quality standards that align with high-performance and low-power goals


• Own and evolve the RTL flow and build system, including support for an agentic AI workflow


• Contribute to a broader portfolio of software initiatives: the RTL CI/CD system, operational metrics collection and reporting, custom web application development, and open-source tool provisioning


• Empower design and DV teams to work efficiently by removing friction from front-end workflows and proactively addressing methodology gaps


• Drive front-end RTL implementation methodologies for GPU and SoC designs, ensuring scalability, architectural alignment, and adherence to performance and power objectives


• Take ownership of moderate-to-complex projects, leading efforts to advance best practices and staying ahead of industry trends and emerging technologies

Requirements

• 6+ years of experience with a Bachelor’s Degree in Computer Science/Engineering, or 4+ years of experience with a Master’s Degree, or 2+ years of experience with a Ph.D.


• Hands-on experience designing and building agentic AI tools and workflows


• Proficiency across a broad range of Unix/Linux programming languages, including Python, C++, Perl, Ruby, Go, and shell scripting


• Deep Linux system expertise, including debugging complex system-level issues


• Solid background in DevOps practices, build automation, and build systems, including GNU Make


• Experience with containerized environments and orchestration platforms, including Docker, Kubernetes, and OpenShift


• Strong analytical and problem-solving skills with a methodical approach to debugging


• Excellent written and verbal communication skills, with a track record of producing clear technical documentation, design specs, and methodology guides


• Proven ability to collaborate effectively across global, cross-functional teams and thrive in fast-paced, ambiguous environments


• Familiarity with RTL design concepts and testbench environments is a plus.

Core Competencies

Demonstrates expertise in front-end RTL implementation methodologies for GPU and SoC designs, with a strong focus on scalability, performance, and power objectives. Proficient in developing agentic AI tools and workflows, while fostering collaboration across design and verification teams to enhance efficiency and uphold best practices.

Highest-signal resume keywords

• Front-End RTL Implementation


• Agentic AI Tools Development


• Unix/Linux Programming (Python, C++, Perl, Ruby, Go)


• DevOps Practices and Build Automation


• Containerization (Docker, Kubernetes, OpenShift)