Advance Google Cloud's expansion by ensuring efficient and timely network capacity delivery to support our products and customers. This role blends a profound understanding of network fundamentals with cutting-edge machine learning and AI methodologies. You will be instrumental in scaling forecasting, automating anomaly detection, and simulating intricate capacity scenarios to meet future demands.

As a vital technical collaborator, you'll work alongside Technical Account Managers, Customer Engineers, and Product Managers. Your focus will be on navigating customer requirements, proactively mitigating supply stockouts, and expertly managing inventory buffers. The objective is to strike a crucial balance between resource efficiency and maintaining high availability, thereby safeguarding infrastructure performance and driving strategic demand attainment across our global network.

Utilize comprehensive knowledge of network fundamentals to identify critical paths, adeptly manage complex customer requirements, and collaboratively develop bespoke solutions with Technical Account Managers, Customer Engineers, and Product Managers.

Take ownership of the execution window, effectively capturing large agreement requirements and navigating intricate network lead times.

Develop advanced forecasting models by leveraging machine learning and AI to enhance predictive accuracy, automate anomaly detection processes, and simulate various capacity scenarios.

Proactively mitigate supply shortages, maintain optimal inventory levels, implement policy-based buffers, and strategically plan for significant peak traffic events.

Collaborate on building AI-assisted automation for streamlined ordering and resource fulfillment, concurrently designing key metrics to monitor fleet efficiency and demand attainment.

Requires a Bachelor's degree or equivalent practical experience, coupled with a minimum of 5 years in program management. Additionally, a minimum of 5 years of experience in designing, constructing, or managing infrastructure projects is essential. Demonstrated experience in creating infrastructure designs, including telecom, electrical, and mechanical systems, as well as producing drawing sets for data center networking space builds and remodels, is a key requirement.

Preferred qualifications include experience partnering with Data Science teams or actively utilizing machine learning and AI methodologies for scaling forecasting models, automating anomaly detection, and simulating capacity scenarios. Expertise in network capacity planning, demand forecasting, inventory optimization, or supply-demand matching is highly valued. Proficiency in data modeling, trend analysis, statistics, and data tools like SQL and spreadsheet software for synthesizing complex capacity metrics and performance loops is expected. A strong foundational understanding of network infrastructure concepts, such as network routing, peering, cache infrastructure (CDN), or capacity placement, is also beneficial.