Design, prototype, and deploy AI-powered solutions that improve debug efficiency, reduce manual effort, and accelerate root-cause analysis.
Develop agentic workflows, copilots, MCP integrations, RAG systems, and AI assistants for semiconductor debugging use cases.
Build proof-of-concepts and production-ready solutions using LLMs, AI agents, and automation frameworks.
Translate semiconductor debug workflows into scalable software and AI solutions.
Analyze logs, reports, register data, validation results, and other engineering artifacts to develop intelligent troubleshooting capabilities.
Drive shift-left initiatives by enabling earlier defect detection, readiness validation, and automated diagnostics.
Work closely with software, firmware, validation, and silicon teams to deploy solutions into daily engineering workflows.
Measure business impact through productivity improvements, cycle-time reduction, and readiness acceleration.
Evangelize AI best practices and help engineers adopt AI-first workflows.
Required experience
Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field.
5-8 years of software engineering, automation, validation, or semiconductor engineering experience.
Strong programming skills in Python.
Experience developing enterprise applications, automation solutions, or engineering tools.
Hands-on experience with Generative AI technologies including
LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.)
Agentic AI frameworks
MCP (Model Context Protocol)
Retrieval Augmented Generation (RAG)
Vector databases and embeddings
Prompt engineering and evaluation
Experience building APIs, automation workflows, and integrations.
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management abilities.
Preferred Experience
Experience in semiconductor debugging, silicon validation, bring-up, or DFT/debug environments.
Familiarity with scan, JTAG, registers, validation logs, silicon debug, or post-silicon workflows.
Experience with SoC architecture, debug tools, firmware validation, or hardware/software co-debug.
Knowledge of GitHub Copilot, AI coding assistants, and developer productivity tools.
Experience deploying AI solutions in production environments.
Familiarity with data engineering, knowledge graphs, and search technologies.
#LI-RG2
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.
AI Solutions Engineer – Debug Tools
The Role
We are looking for a highly motivated AI Solutions Engineer to help transform how semiconductor debugging and tool readiness are delivered through AI-powered solutions. In this role, you will work directly with debug tools developers, architects, and SoC engineers to identify high-impact engineering problems and rapidly develop AI-driven solutions that improve productivity, accelerate bring-up activities, and shift-left debug readiness.
The Person
You will serve as the bridge between engineering teams and AI technologies, turning complex debugging workflows into scalable AI-enabled experiences. The ideal candidate combines strong technical problem-solving skills, software development expertise, and a passion for applying modern AI technologies to real-world challenges.
Key Responsibilities
Partner with debug tools leads, debug teams/key users to identify engineering bottlenecks and automation opportunities.
Design, prototype, and deploy AI-powered solutions that improve debug efficiency, reduce manual effort, and accelerate root-cause analysis.
Develop agentic workflows, copilots, MCP integrations, RAG systems, and AI assistants for semiconductor debugging use cases.
Build proof-of-concepts and production-ready solutions using LLMs, AI agents, and automation frameworks.
Translate semiconductor debug workflows into scalable software and AI solutions.
Analyze logs, reports, register data, validation results, and other engineering artifacts to develop intelligent troubleshooting capabilities.
Drive shift-left initiatives by enabling earlier defect detection, readiness validation, and automated diagnostics.
Work closely with software, firmware, validation, and silicon teams to deploy solutions into daily engineering workflows.
Measure business impact through productivity improvements, cycle-time reduction, and readiness acceleration.
Evangelize AI best practices and help engineers adopt AI-first workflows.
Required experience
Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field.
5-8 years of software engineering, automation, validation, or semiconductor engineering experience.
Strong programming skills in Python.
Experience developing enterprise applications, automation solutions, or engineering tools.
Hands-on experience with Generative AI technologies including
LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.)
Agentic AI frameworks
MCP (Model Context Protocol)
Retrieval Augmented Generation (RAG)
Vector databases and embeddings
Prompt engineering and evaluation
Experience building APIs, automation workflows, and integrations.
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management abilities.
Preferred Experience
Experience in semiconductor debugging, silicon validation, bring-up, or DFT/debug environments.
Familiarity with scan, JTAG, registers, validation logs, silicon debug, or post-silicon workflows.
Experience with SoC architecture, debug tools, firmware validation, or hardware/software co-debug.
Knowledge of GitHub Copilot, AI coding assistants, and developer productivity tools.
Experience deploying AI solutions in production environments.
Familiarity with data engineering, knowledge graphs, and search technologies.
#LI-RG2
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.
