Head of NeoCloud TPUaaS/GPUaaS Leasing

About the role

The Program Lead for NeoCloud TPUaaS/GPUaaS Leasing Business drives the strategy, operations, and commercial success of our chip capacity leasing program. In this role, you will architect the end-to-end program, direct leasing initiatives, and secure high-value agreements to scale our hardware infrastructure as a service. You will define the multi-year strategy, turning capabilities into market-leading commercial offerings. Leading a cross-functional team, you will drive compute capacity leasing, infrastructure allocation, and agreement negotiations to maximize Tensor Processing Unit (TPU) and Graphics Processing Unit (GPU) fleet utilization and business.

You will serve as the primary interface with executive technical leadership and sales teams to align global capacity, while building alliances with AI startups and representing NeoCloud to premier clients and cloud partners.

Responsibilities

• Architect the multi-year NeoCloud TPUaaS/GPUaaS strategy, translating complex AI hardware requirements into commercially viable leasing packages.
• Structure and discuss complex Hardware-as-a-Service (HaaS) capacity agreements to meet business demand and business goals.
• Build executive relationships with NeoClouds, AI startups, and ecosystem partners to secure long-term utilization commitments.
• Own end-to-end financial impact, aligning leasing, capacity scheduling, and infrastructure allocation with global efficiency goals.
• Direct and coach cross-functional teams, cultivating a high-accountability culture focused on customer-centric technical excellence.

Requirements

• Bachelor's degree or equivalent practical experience.
• 14 years of experience in business development or commercial negotiations within cloud computing, infrastructure-as-a-service, or technology hardware industries.
• 5 years of experience in people management, leading cross-functional teams or managing structured program offices.
• Experience structuring or executing enterprise commercial agreements or hardware leasing agreements.

Preferred qualifications

• Advanced degree (e.g., MBA, MS in Computer Science/Engineering) in a related tech, or business field.
• Deep, demonstrable expertise across AI/ML infrastructure, including TPU/GPU compute topologies, cloud scaling architectures, and capacity planning.
• Exceptional ability to influence cross-functional technical and business executives, translating hardware roadmaps into scalable commercial solutions.
• Established network within the AI development ecosystem, including venture-backed enterprise AI companies and hyper-scale tech partners.

Benefits

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $222000 - $309000 (USD) + 25% bonus target + equity + benefits