Lead Quality Platform Engineering

WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

THE ROLE: 

In this role, you will provide quality and DevOps engineering support for AMD's GPU-accelerated ML libraries powering AI, LLM, and deep learning applications. You will be responsible for developing and executing comprehensive CI/CD pipelines, automated test suites, ETL data systems, and observability dashboards that validate library correctness across GPU architectures. You will work closely with library developers, platform teams, and program management to ensure stability, reliability, and performance via both automated pipelines and hands-on testing.

THE PERSON: 

We are seeking a senior developer with a strong quality and automation mindset to join our Quality DevOps. If you're passionate about building robust CI systems, data-driven quality metrics, test-driven development, and enabling validation at scale — this is an excellent opportunity to make a significant impact on AMD's GPU software readiness.

 

KEY RESPONSIBILITIES: 

• Test Automation Development: Design, implement, and maintain automated test suites using gtest for an open-source, C++-based library. 
• CI/CD Integration: Integrate test automation frameworks into the GitHub Actions pipeline, ensuring seamless execution of tests and rapid feedback for developers.
• Tooling: Drive the scaling out of our common platform to collect and visualize Quality metrics, taking a data-driven approach to surfacing engineering health
• Bug Detection & Reporting: Identify, isolate, and report defects found during testing and work with developers to prioritize and resolve issues. 
• Continuous Improvement: Continuously improving the test infrastructure and methodologies, proposing tools or techniques that can improve the testability of the codebase. 
• Collaboration & Documentation: Work with cross-functional teams, document test results, and assist in creating user-friendly reports that communicate the quality status of the project. 
• Test Planning: Collaborate with developers and product teams to define test strategies, test cases, and acceptance criteria for new features and enhancements in the library. 
• Code Coverage: Develop and analyze solutions, identify gaps, and drive improvements in both test coverage and quality.
• Debugging & Root Cause Analysis: Lead complex debugging across the stack (kernel → library → framework), driving systematic resolution and preventing recurring issues.
  
  
  

• B.Tech/M.Tech in Computer Science, Electrical/Electronic Engineering, or related field
• 10+ years of experience in DevOps, CI/CD, or infrastructure engineering
• Proven experience as an SDET or in a similar role with a focus on C++ development and testing.
• Strong experience with GoogleTest (gtest) for unit and integration testing in C++.
• Hands-on experience with Jenkins or GitHub Actions for automating test execution and integrating tests into CI/CD pipelines.
• In-depth knowledge of software testing methodologies, frameworks, and tools for automated testing.
• Experience working in Windows and Linux-based environments for development and testing.
• Familiarity with Docker or other containerization for managing test environments and consistent test execution.
• Familiarity with version control systems such as Git, and with development tools and practices common in open-source communities.
• Familiarity with building/deploying web apps for the purpose of dashboarding and/or visualization
• Excellent problem-solving skills and a proactive approach to testing and debugging.
• Strong written and verbal communication skills, with the ability to collaborate effectively with both technical and non-technical teams.
• Experience leveraging agentic AI to automate multi-step engineering workflows such as CI orchestration, test generation, or incident remediation.
  
  
  

• Experience with ROCm/CUDA, HIP, or GPU compute stacks
• Proficiency in C++, including memory management, data structures, and algorithms.
• Familiarity with pre-silicon simulation environments (functional models, emulators)
• Experience with GPU kernel compilation workflows and binary artifact management
• Knowledge of JIRA/Confluence integration for traceability and automation
• Experience with observability patterns (metrics, alerting, SLA monitoring)
• Familiarity with HSA runtime, GPU driver stacks (KMD/UMD), or DTIF environments