• Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics).

• Iterate on ideas, conducting rapid A/B testing and proof-of-concept experiments to validate the technical feasibility and business impact of agent-based solutions.

• Create comprehensive documentation, including technical specifications, model architecture, and model maintenance procedures to ensure a seamless and efficient transition of successful prototypes to production engineering teams. Run regression tests in production to validate model outcomes.

• Partner closely with Supply Chain Operations, Architects, Finance, and Engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production.

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

• Bachelor's degree in Computer Science, Engineering, Mathematics, Operations Research, or a related quantitative field.

• 2 years of experience in developing and deploying Machine Learning models or AI-driven applications.

• Experience with agent-based modeling, predictive modeling, or deep learning architectures.

• Experience with prompt engineering.