Fellow, AI Systems Architect for Operations

Responsibilities

• Define and execute ARM’s long-term vision and strategy for Agentic AI across engineering and product operations.
• Architect and deploy enterprise-scale Multi Agentic AI platforms applying LLMs, SLMs, RAG, Knowledge Graphs, MCP frameworks, and modern agent orchestration technologies.
• Drive AI-enabled transformation across the complete semiconductor lifecycle, including:
• Architecture & Design
• Functional Verification & Emulation
• DFT & Test Content Development
• Product & Test Engineering
• ATE Program Development
• Yield Learning & Diagnosis
• Reliability & Quality Engineering
• Failure Analysis
• Product Operations
• Supply Chain Management
• Identify and prioritize high-impact AI automation opportunities that deliver measurable improvements in productivity, quality, cycle time, and operational efficiency.
• Establish enterprise AI governance, security, deployment, and adoption guidelines.
• Collaborate across engineering, operations, IT, and executive leadership teams to drive company-wide AI initiatives.
• Mentor engineers and technical leaders while fostering a culture of innovation and AI excellence.
• Represent ARM externally through industry conferences, publications, patents, and strategic partnerships.

Required Skills and Experience

• Master's or Ph.D. in fields such as Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical area.
• Minimum 20 years of semiconductor proven experience.
• Hands-on experience developing and deploying Multi-Agent AI systems in production environments.
• Proven technical leadership across multiple areas including:
• Semiconductor Design & Verification
• Design-for-Test (DFT)
• Silicon Validation
• Product & Test Engineering
• Yield Engineering
• Quality & Reliability Engineering
• Failure Analysis
• Manufacturing & New Product Introduction (NPI)
• Strong expertise in:
• Agentic AI Architectures
• Generative AI
• Large Language Models (LLMs)
• Small Language Models (SLMs)
• Retrieval-Augmented Generation (RAG)
• Knowledge Graphs
• Machine Learning & Deep Learning
• AI Workflow Orchestration Frameworks
• Experience building enterprise automation platforms and integrating with engineering, manufacturing, and business systems.
• Outstanding communication, technical leadership, and collaborator management skills.

Preferred Qualifications

• Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, or related field, or an equivalent level of experience.
• Three or more sophisticated AI/ML certifications in areas such as:
• Agentic AI
• Generative AI
• Machine Learning
• Deep Learning
• RAG Systems
• Knowledge Graphs
• AI Engineering
• Experience building AI-enabled automation solutions for semiconductor design, verification, DFT, product engineering, quality, or manufacturing workflows.
• Experience with LangGraph, LangChain, AutoGen, CrewAI, MCP, or similar multi-agent frameworks.
• Experience integrating AI systems with EDA tools and engineering data ecosystems.
• Experience in one or more pre-silicon fields including RTL Build, Functional Verification, Emulation, FPGA Prototyping, Physical Compose, Timing Closure, Low-Power Develop, or SoC Integration.
• Publishations, patents, or invention disclosures in AI, coordinated circuit development, validation, test, quality, reliability, or manufacturing.
• Demonstrated success leading enterprise-wide technology transformation initiatives.
• Experience deploying secure on-premise AI platforms for engineering applications.