Intern - PLN IE

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Project Title Agentic AI–Driven Intelligent Planning Ecosystem for Fab Space and Capacity Optimization   Project Description This internship project focuses on the development of an Agentic AI-enabled planning ecosystem to enhance fab space utilization, tool placement planning, and decision-making across the Planning (PLN) domain. The intern will have the opportunity to contribute to the design and evaluation of an intelligent multi-agent framework that supports planning optimization through data-driven analysis and Artificial Intelligence technologies.   The project will explore the use of Agentic AI architecture and Google SDK technologies to coordinate multiple specialized AI agents, including: Industrial Engineering (IE) Agent for tool demand forecasting and capacity planning Layout Agent for space allocation analysis and constraint evaluation Material and Spare Planning Agent for resource planning optimization Operations Modelling Agent for scenario simulation and planning insights Cost/Capex Agent for investment and cost optimization assessments   Through collaboration with planning stakeholders, the intern will gain exposure to AI-enabled planning methodologies, multi-agent reasoning frameworks, optimization techniques, and large-scale manufacturing planning challenges.   Objective of the Project The objective of this project is to evaluate how Agentic AI solutions can improve planning effectiveness by enabling coordinated decision-making across multiple planning domains. The project aims to identify opportunities to optimize fab capacity utilization, improve planning alignment, and enhance future-state scenario evaluation through intelligent agent collaboration.   Opportunities for Full Time Employment Successful completion of the internship may provide opportunities to be considered for future full-time roles, subject to business requirements, performance, and available openings.   Project Scope The intern will have opportunities to: Study existing planning workflows and data inputs across the PLN domain. Develop proof-of-concept Agentic AI workflows for planning optimization. Evaluate coordination mechanisms between multiple specialized AI agents. Analyze planning trade-offs involving tool demand, factory layout constraints, material requirements, operational scenarios, and capital investment considerations. Explore AI-Enabled approaches for generating planning recommendations and scenario-based decision support. Document findings, recommendations, and improvement opportunities.   Learning Opportunities The intern will gain hands-on experience in: Agentic AI and multi-agent system design Generative AI and Large Language Model (LLM) applications Manufacturing planning and capacity optimization methodologies Operations research and optimization techniques Data analytics and scenario modelling AI-enabled decision support systems Cross-functional collaboration within semiconductor manufacturing environments   Deliverables Agentic AI planning ecosystem proof-of-concept or prototype Multi-agent workflow design documentation Planning optimization analysis and scenario evaluation results Recommendations for space utilization, tool placement, and planning improvements Final project presentation summarizing findings and future enhancement opportunities   Impact of the Project This project aims to demonstrate how Agentic AI technologies can contribute to improved planning effectiveness by enabling coordinated,