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. THE ROLE: As an AMD-AECG Design Automation Engineer, you will help build the next generation of AI-powered engineering platforms that enable AMD's chip design teams to find, understand, and interact with complex semiconductor design data. You will develop scalable software systems, data pipelines, knowledge graphs, and AI/LLM-driven capabilities that transform how architects, designers, and verification engineers access and leverage engineering knowledge. Working at the intersection of AI, software infrastructure, and semiconductor design, you will help expand the platform to support new engineering domains, workflows, and agent-based experiences that accelerate chip development. THE PERSON: The ideal candidate is a strong software engineer with experience building production-quality backend systems and a passion for applying AI to solve complex technical problems. You are comfortable designing data models, building large-scale data pipelines, and developing AI/LLM-based solutions such as retrieval systems, knowledge graphs, and agentic workflows. You thrive in highly technical and ambiguous environments, can collaborate effectively with both software and hardware engineers, and are motivated by the opportunity to build tools that directly impact the design of next-generation CPUs, GPUs, and AI accelerators. KEY RESPONSIBILITIES: • Design, build, and maintain backend data pipelines that turn engineering data sources into structured, quarriable representations • Design and evolve data schemas and queries to support new engineering data types and use cases at production scale • Build and extend AI/LLM-based components that let engineers query and interact with engineering data using natural language • Diagnose and fix reliability and performance issues in distributed batch-processing pipelines handling large volumes of data • Design and implement new data pipelines to bring additional engineering data domains onto the platform • Tune LLM-based components for accuracy, cost, and latency • Own a TDD-driven development workflow using the team's version control and code review practices • Collaborate with architecture, verification, and design teams to translate their data and workflow needs into platform capabilities PREFERRED EXPERIENCE: • Strong Python engineering background, with rigorous testing discipline (unit/integration/end-to-end) in a large, shared codebase • Experience with graph databases and/or vector search systems, including schema design and query performance for retrieval workloads • Experience with LLM-based/agentic systems: retrieval-augmented generation, agent orchestration frameworks, tool-use/function-calling, and awareness of LLM cost/latency/token tradeoffs • Familiarity with RTL/HDL/Physical Design semantics (SystemVerilog/Verilog/SW/HW modeling, module hierarchy, instantiation, parameters) and toolchains for parsing/elaborating hardware design source • Experience with time-series/relational data stores and reasoning about consistency across multiple database backends • Strong written and verbal communication skills ACADEMIC CREDENTIALS: Bachelors/Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field. This role is not eligible for visa sponsorship. #LI-DR2 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.
Design, build, and maintain backend data pipelines that turn engineering data sources into structured, quarriable representations
Design and evolve data schemas and queries to support new engineering data types and use cases at production scale
Build and extend AI/LLM-based components that let engineers query and interact with engineering data using natural language
Diagnose and fix reliability and performance issues in distributed batch-processing pipelines handling large volumes of data
Design and implement new data pipelines to bring additional engineering data domains onto the platform
Tune LLM-based components for accuracy, cost, and latency
Own a TDD-driven development workflow using the team's version control and code review practices
Collaborate with architecture, verification, and design teams to translate their data and workflow needs into platform capabilities
Benefits offered are described: AMD benefits at a glance .
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.

Nice-to-haves

Strong Python engineering background, with rigorous testing discipline (unit/integration/end-to-end) in a large, shared codebase
Experience with graph databases and/or vector search systems, including schema design and query performance for retrieval workloads
Experience with LLM-based/agentic systems: retrieval-augmented generation, agent orchestration frameworks, tool-use/function-calling, and awareness of LLM cost/latency/token tradeoffs
Familiarity with RTL/HDL/Physical Design semantics (SystemVerilog/Verilog/SW/HW modeling, module hierarchy, instantiation, parameters) and toolchains for parsing/elaborating hardware design source
Experience with time-series/relational data stores and reasoning about consistency across multiple database backends
Strong written and verbal communication skills
ACADEMIC CREDENTIALS: Bachelors/Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.

Application prep

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Keywords to mirror

aillmpython

Platform: amd
Effort: medium