Compute Resource Technical Operations Manager (GPU Supply Chain)

About the role

Tencent Cloud, within the Cloud & Smart Industries Group (CSIG), is looking for a Compute Resource Technical Operations Manager based in Singapore. The role covers the planning, procurement and delivery of GPU compute resources, including forecasting demand, coordinating suppliers and ensuring end-to-end acceptance of compute clusters.

Key responsibilities

• Forecast GPU compute service demand based on MaaS business development, model evolution and resource utilization, and formulate resource portfolios, supply scales and delivery plans that balance cost, efficiency and supply stability.
• Take part in GPU compute service procurement, work with procurement and technical teams on specifications, service standards and acceptance requirements, assess supplier delivery capability and follow up on resource arrival, service launch and issue closure.
• Track market supply and demand, supplier capacity and geopolitical compliance risks, build multi-supplier and cross-region resource assurance plans, and manage capacity reservations and reserves to avoid supply interruptions and idle resources.
• Collaborate with technical teams on GPU selection and evaluation of data center, network and storage solutions, and follow up end-to-end on delivery, performance testing and acceptance against model deployment and inference service requirements.

Required profile

• 10+ years of experience in large-scale IT infrastructure, compute resource delivery, sourcing or supply chain management, with a complete project track record in resource planning, procurement collaboration and delivery management.
• Professional fluency in English and Mandarin, as about half the role involves working with the headquarters team in China.
• Preferred: experience in compute resource operations, compute procurement or large-scale compute cluster delivery at cloud providers or leading large-model companies.

Required skills

• Familiarity with the AI chip market supply landscape, supplier and channel systems, and ability to assess availability, lead times and supply risks.
• Knowledge of AI computing servers, data centers, networks and storage, and of deployment conditions, delivery processes and acceptance standards of large compute clusters.
• Understanding of large-model deployment and inference services, including token metering, billing methods and metrics such as throughput, latency and concurrency.
• Strong data analysis, cost modeling and cross-team collaboration skills.