Lead Engineer - AI role at AMD: As an Artificial Intelligence Engineer (MTS) within AMD’s IP organization, you will own and drive AI-powered tools, platforms, and methodologies that significantly improve RTL design and verification productivity, quality, and scalability. The role focuses on AI-assisted engineering solutions, process transformation, and enterprise-scale automation, operating parallel to RTL and Verification teams rather than direct hardware design. You will lead technical direction, influence methodology, and deliver production-ready AI solutions adopted across multiple IP teams, including building and integrating AI tools into EDA workflows and CI/CD pipelines. Mentorship and cross-team collaboration are key to driving adoption and scalable AI across the organization.
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. Artificial Intelligence Engineer (Member of Technical Staff Role Overview As an Artificial Intelligence Engineer (MTS) within AMD’s IP organization, you will own and drive AI-powered tools, platforms, and methodologies that significantly improve RTL design and verification productivity, quality, and scalability. This role operates parallel to RTL and Verification teams, focusing on AI-assisted engineering solutions, process transformation, and enterprise-scale automation, rather than direct hardware design or verification. At the MTS level, you are expected to lead technical direction, influence methodology, and deliver production-ready AI solutions adopted across multiple IP teams. Key Responsibilities Technical Ownership & Architecture Own the architecture and roadmap for AI-based productivity tools supporting: RTL development Design verification IP quality and signoff flows Drive end-to-end solutions from problem definition → deployment → adoption Make architectural decisions on: Model selection (ML vs LLM vs hybrid) Data pipelines Tool integration strategy AI Tools & Automation Development Design and implement production-grade AI tools for: Regression failure clustering and triage Intelligent log analysis and anomaly detection Automated lint/CDC/RDC issue classification AI-assisted debug and root-cause analysis Build context-aware AI assistants for RTL and DV engineers Process & Infrastructure Integration Integrate AI solutions into: EDA workflows CI/CD and regression systems Version control and review pipelines Partner with: RTL, DV, CAD, and IT teams Ensure scalability, security, and reliability of deployed tools Data, Models & MLOps Define and maintain data strategies using: Simulation logs Coverage databases Static analysis reports Lead: Model training, fine-tuning, and evaluation MLOps practices (monitoring, retraining, versioning) Establish metrics for: Productivity improvement Debug time reduction Quality uplift Adoption, Mentorship & Influence Drive adoption through: Documentation and training Feedback-driven iterations Mentor junior engineers Influence methodology standards across IP teams Required Qualifications Education B.E./B.Tech or M.E./M.Tech in: Computer Science Electrical / Electronics Engineering Data Science / AI (with strong systems background) Experience 5–8+ years of experience in: AI/ML tools development or EDA methodology / automation or Software engineering for hardware organizations Strong working knowledge of RTL and Verification workflows (user and methodology level) Technical Skills Expert-level programming in: Python C++ or Java (preferred) Strong experience with: Machine learning, NLP, and LLM-based systems Data engineering and feature pipelines Familiarity with: RTL (SystemVerilog) and UVM concepts — methodology-level EDA tools and flows (lint, CDC, simulation, regressions) Experience integrating AI tools into large engineering organizations Preferred / Nice-to-Have Skills Experience building: AI copilots for engineering teams Log intelligence and analytics platforms Exposure to: CI/CD systems (Jenkins, GitLab) MLOps platforms Knowledge of: IP reuse and signoff processes Security and compliance for internal tools Soft Skills Strong technical leadership without direct authority Ability to translate engineering pain points into scalable AI solutions Clear communication across hardware, software, and management teams Bias for action and delivery #LI-SR5 Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.