Fellow, AI Systems Architect for Operations

Job Title

Fellow, AI Systems Architect for Operations

Role Summary

Senior technical leader responsible for defining and delivering enterprise-scale autonomous and multi-agent AI systems that transform engineering, product operations, and supply chain workflows across the semiconductor lifecycle. Lead strategy, architecture, governance, deployment, and adoption of AI-driven automation across verification, test, manufacturing, reliability, and product operations.

Experience Level

Senior — minimum 20 years of semiconductor experience with extensive technical leadership and hands-on AI systems delivery.

Responsibilities

Drive strategy and delivery of Agentic AI across engineering and operations. Collaborate with cross-functional teams and mentor technical leaders.

• Define and execute long-term vision and strategy for agentic AI in engineering and product operations.
• Architect and deploy enterprise-scale multi-agent AI platforms using LLMs/SLMs, RAG, knowledge graphs, MCP frameworks, and agent orchestration.
• Identify and prioritize high-impact AI automation opportunities that improve productivity, quality, cycle time, and operational efficiency.
• Establish enterprise AI governance, security, deployment, and adoption guidelines.
• Drive AI transformation across architecture & design, verification & emulation, DFT, product & test engineering, yield learning, reliability, failure analysis, product operations, and supply chain.
• Collaborate with engineering, operations, IT, and executive leadership to deliver company-wide AI initiatives.
• Mentor engineers and technical leaders and represent the company externally at conferences, publications, patents, and partnerships.

Requirements

Must-have technical skills, domain experience, and leadership capabilities. Preferred items are marked as nice-to-have.

• Must-have: Minimum 20 years of semiconductor industry experience with proven technical leadership across multiple domains (design & verification, DFT, silicon validation, product & test engineering, yield, quality & reliability, failure analysis, manufacturing/NPI).
• Must-have: Hands-on experience developing and deploying multi-agent AI systems in production.
• Must-have: Strong expertise in agentic AI architectures, generative AI, large & small language models, retrieval-augmented generation (RAG), knowledge graphs, and ML/DL.
• Must-have: Experience with AI workflow orchestration frameworks and building enterprise automation platforms integrated with engineering, manufacturing, and business systems.
• Must-have: Outstanding communication, technical leadership, and collaboration skills.
• Nice-to-have: Experience with LangGraph, LangChain, AutoGen, CrewAI, MCP or similar multi-agent frameworks, and integration with EDA tools and engineering data ecosystems.
• Nice-to-have: Experience deploying secure on-premise AI platforms for engineering applications and leading enterprise-wide transformation initiatives.
• Nice-to-have: Publications, patents, or invention disclosures related to AI or semiconductor engineering and test.

Education Requirements

Master's or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical field. Ph.D. is preferred but an equivalent level of experience is accepted. Candidates with multiple advanced AI/ML certifications (the posting cites three or more) are also noted as preferred.

About the Company

Company: Arm

Headquarters: Cambridge, United Kingdom

ARM is a global leader in semiconductor and software design, driving innovation in computing technology. The company specializes in designing processors and systems that provide the essential building blocks for electronic devices. ARM's architecture is widely used in smartphones, servers, and IoT devices, and its collaborative culture fosters bold thinking, diversity, and high-impact benefits for its talented workforce.