Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career. ABOUT THE DEPARTMENT: Central DFX (CDFX) is a centralized ASIC design organization within AMD Technology and Engineering, with teams across North America and Asia. CDFX develops and standardizes Design-for-Test (DFT) and Design-for-Debug (DFD) architectures, methodologies, implementation flows and CAD automation for high-performance and adaptive-compute products serving data center, embedded, gaming and PC markets. THE ROLE: We are seeking an AI/ML Project Lead who combines deep DFT design and methodology expertise with hands-on experience developing production-quality AI solutions and agentic engineering workflows. This technical leadership role will define and drive a portfolio of AI-enabled capabilities that improve the productivity, quality, scalability and predictability of DFX design and verification flows. THE PERSON: You will partner with DFT, DFD, CAD, design, verification and software engineering teams to identify high-value use cases, translate engineering knowledge into deployable solutions, and lead projects from concept and prototype through production deployment, adoption and sustained operation. The role requires strong technical judgment across semiconductor design, AI/ML, software architecture and program execution. KEY RESPONSIBILITIES: • Lead the strategy, roadmap and execution of AI/ML and agentic AI initiatives for DFT and DFD design, methodology, verification and debug workflows. • Integrate AI agents and services with DFX design flows, EDA tools, repositories, specifications, regression systems and engineering data sources through secure, maintainable interfaces. • Develop AI-enabled expert systems, predictive models and intelligent automation to address DFT challenges across IP, subsystem and SoC design environments. • Maintain awareness of advancements in AI/ML, agentic systems and semiconductor design automation, and evaluate their relevance to AMD DFX needs. • Identify and prioritize use cases based on measurable engineering value, technical feasibility, data readiness, deployment risk and opportunities for reuse across teams. • Architect agentic workflows that combine large language models, domain knowledge, retrieval, tools, automation and human-in-the-loop controls to support complex engineering tasks. • Establish evaluation methods, quality gates, guardrails, traceability and fallback mechanisms appropriate for production engineering workflows. • Lead model and application deployment, monitoring, incident response, maintenance and continuous improvement using sound MLOps, DevOps and software lifecycle practices. • Drive scalable DFT implementation and verification automation using Python, Perl, Tcl and shell scripting within complex ASIC design environments. • Coordinate cross-functional project plans, dependencies, risks, milestones and technical decisions, and communicate progress clearly to engineering and leadership stakeholders. • Mentor engineers, promote reusable architecture and coding practices, and build organizational capability in responsible AI-assisted engineering. REQUIRED SKILLS AND EXPERIENCE: • Extensive experience in DFT and/or DFD architecture, design, implementation, verification or methodology for high-performance SoCs and IP. • Demonstrated technical leadership of complex, cross-team engineering initiatives from definition through production adoption. • Hands-on experience developing and deploying AI/ML applications in production or enterprise engineering environments. • Familiar with agentic AI systems design, including tool use, multi-agent/subagent systems, Model Context Protocol (MCP), workflow orchestration, Retrieval-Augmented Generation (RAG), structured outputs, evaluation and human oversight. • Experience designing agentic AI systems, including tool use, workflow orchestration, retrieval-augmented generation, structured outputs, evaluation and human oversight. • Strong Python development skills and experience with relevant AI/ML frameworks and libraries. Familiarity with scikit-learn, PyTorch, TensorFlow or equivalent technologies is desirable. • Experience with software engineering and deployment practices such as source control, code review, automated testing, CI/CD, APIs, containers and observability. • Knowledge of MLOps and data lifecycle practices, including data quality, model evaluation, versioning, monitoring and reproducibility. • Proficiency with one or more ASIC/EDA automation languages, including Perl, Tcl and shell scripting. • Strong foundation in digital logic, VLSI design and the interactions among test, power, timing, area, physical design and verification constraints. • Proven ability to influence technical direction across organizational boundaries and convert ambiguous problems into executable project plans. PREFERRED QUALIFICATIONS: • Experience integrating AI capabilities with EDA tools, semiconductor design flows or large-scale engineering automation environments. • Experience with knowledge representation, engineering specifications, graph-based data, vector search or domain-specific retrieval systems. • Familiarity with secure AI deployment, responsible AI practices, access controls, intellectual-property protection and auditability. • Python development skills and hands on development experience with relevant AI/ML frameworks and libraries such as Claude SDK / OpenAI SDK. ACADEMIC CREDENTIALS: • BSEE, MSEE, Computer Engineering, Computer Science or an equivalent technical degree preferred. This role is not eligible for visa sponsorship. #LI-MR1 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.

Requirements

Must-haves

ADVANCE YOUR CAREER. ADVANCE THE WORLD.
Lead the strategy, roadmap and execution of AI/ML and agentic AI initiatives for DFT and DFD design, methodology, verification and debug workflows.
Integrate AI agents and services with DFX design flows, EDA tools, repositories, specifications, regression systems and engineering data sources through secure, maintainable interfaces.
Develop AI-enabled expert systems, predictive models and intelligent automation to address DFT challenges across IP, subsystem and SoC design environments.
Maintain awareness of advancements in AI/ML, agentic systems and semiconductor design automation, and evaluate their relevance to AMD DFX needs.
Identify and prioritize use cases based on measurable engineering value, technical feasibility, data readiness, deployment risk and opportunities for reuse across teams.
Architect agentic workflows that combine large language models, domain knowledge, retrieval, tools, automation and human-in-the-loop controls to support complex engineering tasks.
Establish evaluation methods, quality gates, guardrails, traceability and fallback mechanisms appropriate for production engineering workflows.
Lead model and application deployment, monitoring, incident response, maintenance and continuous improvement using sound MLOps, DevOps and software lifecycle practices.
Drive scalable DFT implementation and verification automation using Python, Perl, Tcl and shell scripting within complex ASIC design environments.
Coordinate cross-functional project plans, dependencies, risks, milestones and technical decisions, and communicate progress clearly to engineering and leadership stakeholders.
Mentor engineers, promote reusable architecture and coding practices, and build organizational capability in responsible AI-assisted engineering.
Extensive experience in DFT and/or DFD architecture, design, implementation, verification or methodology for high-performance SoCs and IP.
Demonstrated technical leadership of complex, cross-team engineering initiatives from definition through production adoption.
Hands-on experience developing and deploying AI/ML applications in production or enterprise engineering environments.
Experience designing agentic AI systems, including tool use, workflow orchestration, retrieval-augmented generation, structured outputs, evaluation and human oversight.
Strong Python development skills and experience with relevant AI/ML frameworks and libraries. Familiarity with scikit-learn, PyTorch, TensorFlow or equivalent technologies is desirable.
Experience with software engineering and deployment practices such as source control, code review, automated testing, CI/CD, APIs, containers and observability.
Knowledge of MLOps and data lifecycle practices, including data quality, model evaluation, versioning, monitoring and reproducibility.

Nice-to-haves

Experience integrating AI capabilities with EDA tools, semiconductor design flows or large-scale engineering automation environments.
Experience with knowledge representation, engineering specifications, graph-based data, vector search or domain-specific retrieval systems.
Familiarity with secure AI deployment, responsible AI practices, access controls, intellectual-property protection and auditability.
Python development skills and hands on development experience with relevant AI/ML frameworks and libraries such as Claude SDK / OpenAI SDK.
BSEE, MSEE, Computer Engineering, Computer Science or an equivalent technical degree preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythonci/cd

Platform: amd
Effort: medium