Head of NeoCloud Compute Site Selection and Strategy
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 14 years of experience leading negotiations or business development.
Preferred qualifications:
- MBA or Master's degree in Quantitative Finance, or an advanced Engineering degree.
- Experience within the infrastructure, capacity-planning, or commercial deal teams of a major global hyperscaler or fast-scaling AI NeoCloud provider.
- Familiarity using GIS or data-driven tools for infrastructure mapping and site evaluation.
- Demonstrate a proven track record negotiating wholesale real estate, joint ventures, or colocation structures across international jurisdictions and high-demand AI markets.
About the job
Google's infrastructure needs go far beyond server computers. As Google's products and services scale the globe, the Strategic Negotiation team works behind the scenes to secure infrastructure for Google's future -- everything from underwater cables to physical data center space. As a Strategic Negotiator, you combine your deep market knowledge of a given sector with tech industry savvy to negotiate cost-effective solutions to support Google's infrastructure growth. You'll work with specific project teams on negotiating deals, managing vendor and partner relationships and presenting deal recommendations to our Tech leadership. Your successful negotiations have the potential to save Google millions of dollars in operating costs and impact every part of the business.
As the Head of NeoCloud and Compute-as-a-Service Site Selection and Strategy, you will architect and execute the physical infrastructure roadmap that powers our next-generation AI cloud. NeoCloud environments demand unprecedented high-density power, highly specialized cooling infrastructure, and near-instantaneous speed-to-market.
In this role, you will lead the global sourcing, evaluation, and positioning of our data center footprint, specifically optimized for massive GPU and TPU clusters. Crucially, you will serve as our primary ambassador to the infrastructure ecosystem, focusing on forming key partnerships with emerging NeoClouds and deepening our institutional bench of relationships with utilities, hyperscale landlords, and chip fabrication infrastructure partners.
To be the engine for securing essential, scalable data center capacity and forging proprietary, long-term partnerships. We drive business growth by pioneering first-of-a-kind agreements structures and expertly managing all leasing and data center partnership transactions.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
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
Learn more about benefits at Google.
Responsibilities
- Structure complex, high-value transactions (joint ventures (JVs), leasebacks, asset financing) to minimize capital expenditures (CapEx)/operating expenses (OpEx) and maximize margin profiles.
- Drive financial modeling and discuss flexible terms to mitigate chip architecture shifts and optimize total cost of ownership (TCO)/power usage effectiveness (PUE) efficiency.
- Execute a global, multi-gigawatt site selection strategy optimized for high-density power and ultra-low-latency Tensor Processing Unit (TPU) back-end fabrics.
- Balance megawatt-heavy, low-cost power sites for training with metro-adjacent, low-latency edge clusters for inference.
- Institutionalize executive-level partnerships across utilities, wholesale landlords, and Graphics Processing Unit as a Service (GPU-aaS) providers to fast-track grid connections and share capital burdens.
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