Principal Agentic AI Engineer

About the role

GlobalFoundries is looking for a Principal Agentic AI Engineer to join its Digital Manufacturing AI team and define and lead the next generation of Agentic AI capabilities for semiconductor manufacturing. The role suits a technical leader who connects AI strategy, advanced architecture, manufacturing domain expertise and business value, defining the architecture and technology roadmap for AI agents that evolve from individual assistants into an enterprise-scale ecosystem.

Key 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, and architecture patterns that scale across multiple fabs and use cases.
• Lead exploration of emerging technologies such as 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 and create strategies linking AI capabilities to measurable manufacturing outcomes.
• Mentor a team of AI engineers and architects, establish an internal community of practice and reusable AI-agent platforms, and drive partnerships with technology providers and research institutions.

Required profile

• Master's degree in Computer Science, AI, Machine Learning, Software Engineering or a related discipline, or equivalent experience.
• 7+ years of experience in AI/ML, software engineering, architecture or related technology fields.
• Demonstrated experience designing and deploying enterprise-scale AI systems.
• Preferred: experience in semiconductor, manufacturing, industrial automation or other complex engineering environments.

Required skills

• Strong Python fluency and experience building AI-ready data layers.
• Proficiency in semantic web standards such as RDF and OWL.
• Git, CI/CD pipelines, AWS and REST APIs.
• Deep understanding of Generative AI, LLMs and agentic architectures; familiarity with MCP, tool calling and workflow automation.
• Software architecture and distributed-systems expertise.
• Preferred: AI agents, MCP servers, LangGraph, CrewAI, Redpanda ADP, Semantic Kernel, Pydantic AI, multi-agent systems, and integration with ServiceNow, SAP or Workday.