Fellow, AI Systems Architect for Operations
Arm · Austin, TX · 2 wk ago
HybridEngineering$309k–$418k/yrFull-time
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.
- Publications, 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.