Principal Agentic AI Architect / AI Innovation Lead

GlobalFoundries; Myrtle Point (OR); On-site; USD 180,000 - 260,000; Full time

Job summary

GlobalFoundries seeks a senior Enterprise AI Architect to define the enterprise architecture and technology roadmap for Agentic AI in manufacturing. You will set the technical vision for autonomous AI agents, architect scalable platforms, and establish standards for lifecycle management.

You will lead exploration of advanced reasoning models, multimodal AI, and AI-to-AI collaboration while mentoring a team of AI engineers and architects.

Qualifications

• Master's degree in Computer Science, AI, Machine Learning, Software Engineering or related discipline, or equivalent experience.
• 7+ years of experience in AI/ML, software engineering, architecture or related technology fields.
• High python fluency in writing clean code and handling complex data pipelines.
• Experience in building AI-Ready data layers by establishing model objects, relationships and rules.
• Proficiency in semantic web standards like RDF and OWL
• Experience with Git and CI/CD pipelines.
• Experience with cloud platforms such as AWS and related services.
• Experience developing and consuming REST APIs.
• Deep understanding of Generative AI, LLMs and agentic architectures.
• Familiarity with MCP, tool calling, or workflow automation concepts.
• Strong analytical, debugging, and problem-solving skills.
• Demonstrated experience designing and deploying enterprise-scale AI systems.
• Strong software architecture and distributed-systems expertise.
• Proven ability to translate emerging technology into production business solutions.

Responsibilities

• Define the enterprise architecture and technology roadmap for Agentic AI in manufacturing.
• Establish the technical vision for autonomous and semi-autonomous AI agents across manufacturing domains.
• Architect scalable agent platforms supporting: multi-agent collaboration, agent orchestration, enterprise knowledge, tool and API ecosystems, long-term memory, planning and reasoning.
• Define standards for agent development, evaluation, deployment, monitoring and lifecycle management.
• Establish architecture patterns that allow AI agents to scale across multiple fabs, manufacturing functions and use cases.
• Lead exploration of emerging technologies including advanced reasoning models, multimodal AI, agentic workflows and AI-to-AI collaboration.
• Partner with senior manufacturing, engineering, IT, data and business leaders to identify high-impact opportunities.
• Create technical strategies that connect AI capabilities with measurable manufacturing outcomes.
• Mentor and grow a high-performing team of AI engineers and architects.
• Establish an internal community of practice and reusable AI-agent platforms.
• Drive partnerships with technology providers, research institutions and the broader AI ecosystem.
• Provide technical leadership for the transition from AI assistants → AI agents → autonomous manufacturing workflows.

Skills

Python

LLMs

REST APIs

AWS

Git

CI/CD

RDF/OWL

Semantic web

Multi-agent systems

Agent orchestration

Education

Master's degree in CS/AI/SE or related

Tools

LangGraph

CrewAI

Semantic Kernel

Pydantic AI

Redpanda ADP

Job description

Role overview

Your Job: Define the enterprise architecture and technology roadmap for Agentic AI in manufacturing. Establish the technical vision for autonomous and semi-autonomous AI agents across manufacturing domains. Architect scalable agent platforms supporting: multi-agent collaboration, agent orchestration, enterprise knowledge, tool and API ecosystems, long-term memory, planning and reasoning. Define standards for agent development, evaluation, deployment, monitoring and lifecycle management. Establish architecture patterns that allow AI agents to scale across multiple fabs, manufacturing functions and use cases. Lead exploration of emerging technologies including advanced reasoning models, multimodal AI, agentic workflows and AI-to-AI collaboration. Partner with senior manufacturing, engineering, IT, data and business leaders to identify high-impact opportunities. Create technical strategies that connect AI capabilities with measurable manufacturing outcomes. Mentor and grow a high-performing team of AI engineers and architects. Establish an internal community of practice and reusable AI-agent platforms. Drive partnerships with technology providers, research institutions and the broader AI ecosystem. Provide technical leadership for the transition from AI assistants to AI agents to autonomous manufacturing workflows.

Responsibilities

• Define the enterprise architecture and technology roadmap for Agentic AI in manufacturing.
• Establish the technical vision for autonomous and semi-autonomous AI agents across manufacturing domains.
• Architect scalable agent platforms supporting: multi-agent collaboration, agent orchestration, enterprise knowledge, tool and API ecosystems, long-term memory, planning and reasoning.
• Define standards for agent development, evaluation, deployment, monitoring and lifecycle management.
• Establish architecture patterns that allow AI agents to scale across multiple fabs, manufacturing functions and use cases.
• Lead exploration of emerging technologies including advanced reasoning models, multimodal AI, agentic workflows and AI-to-AI collaboration.
• Partner with senior manufacturing, engineering, IT, data and business leaders to identify high-impact opportunities.
• Create technical strategies that connect AI capabilities with measurable manufacturing outcomes.
• Mentor and grow a high-performing team of AI engineers and architects.
• Establish an internal community of practice and reusable AI-agent platforms.
• Drive partnerships with technology providers, research institutions and the broader AI ecosystem.
• Provide technical leadership for the transition from AI assistants → AI agents → autonomous manufacturing workflows.

Requirements

• Master's degree in Computer Science, AI, Machine Learning, Software Engineering or related discipline, or equivalent experience.
• 7+ years of experience in AI/ML, software engineering, architecture or related technology fields.
• High python fluency in writing clean code and handling complex data pipelines.
• Experience in building AI-Ready data layers by establishing model objects, relationships and rules.
• Proficiency in semantic web standards like RDF and OWL
• Experience with Git and CI/CD pipelines.
• Experience with cloud platforms such as AWS and related services.
• Experience developing and consuming REST APIs.
• Deep understanding of Generative AI, LLMs and agentic architectures.
• Familiarity with MCP, tool calling, or workflow automation concepts.
• Strong analytical, debugging, and problem-solving skills.
• Demonstrated experience designing and deploying enterprise-scale AI systems.
• Strong software architecture and distributed-systems expertise.
• Proven ability to translate emerging technology into production business solutions.

Preferred Qualifications

• Experience with AI agents, MCP servers, LangGraph, CrewAI, Redpanda ADP, Semantic Kernel, Pydantic AI, or similar technologies.
• Deep experience with multi-agent systems and agent orchestration.
• Experience in semiconductor, manufacturing, industrial automation or other complex engineering environments.
• Experience integrating with enterprise APIs (ServiceNow, SAP, Workday).