Chief Technical Officer

Company Overview

Google and Blackstone have partnered to launch a first-of-its-kind AI cloud platform (“TPU Co”), purpose-built around Google’s proprietary Tensor Processing Units (“TPUs”) to deliver the most efficient, reliable, and performant compute infrastructure available. This platform represents one of the first scaled external TPU commercialization efforts for Google’s prized TPU assets, which it has spent over a decade developing. Google’s TPUs have trained and deployed at scale many of the world’s leading frontier AI models including leading models from Google itself and Anthropic. Leading AI technology companies including Meta and Anthropic have continued to signal strong demand for TPU compute, including many billions of dollars of publicly announced commitments.

TPU Co will deploy and operate AI computing clusters and related services for end customers, including hyperscalers, frontier AI labs, sovereign customers, and other leading enterprises and AI technology companies. The JV will develop deep in-house expertise across sourcing and development of data center and power capacity; design, engineering, and deployment of TPU clusters as well as the software required to operate and monitor these clusters; and customer support and success.

TPU Co will be developed in close partnership with Google, providing differentiated access to TPU supply, technical expertise, and infrastructure support. Blackstone will deploy billions of dollars of equity capital, providing unprecedented access to programmatic capital at scale. Together, these relationships position TPU Co to scale capacity rapidly and be a true first mover in defining the next gold standard for AI infrastructure. TPU Co will work hand-in-hand with both Google and its end customers, many of whom will be the leading AI and technology companies in the world, to develop custom, world-class infrastructure that powers the next generation of AI innovation.

Executive Team

TPU Co will be led by CEO Ben Treynor Sloss, who spent over two decades at Google in executive technical and infrastructure leadership roles. Ben founded the Site Reliability Engineering function, now the industry standard for operating large-scale infrastructure systems, and most recently worked directly with Google Cloud CEO Thomas Kurian to drive the commercialization of TPUs.

Ben brings deep domain expertise in AI infrastructure, along with longstanding relationships and credibility across Google’s senior leadership and customer ecosystem. He has been involved in the formation of TPU Co since inception, playing a critical role in shaping the partnership.

The Role

As Chief Technical Officer, you will own the technical stack required to deploy, operate, and scale AI compute infrastructure at world-class reliability and performance. You are responsible for three core functions:

• Site Reliability Engineering (SRE): End-to-end infrastructure software design and operations, ensuring our compute platform delivers industry-best uptime, performance, and efficiency across customer workloads
• Hardware Operations: Deploying, integrating, networking, monitoring, and maintaining accelerator hardware at scale
• Software Platform & Operations: Building and operating the software layer that orchestrates compute workloads, manages cluster scheduling, provides observability, and delivers the customer-facing platform experience

Desired Experiences & Skills

• End to end understanding of infrastructure software design & operations, including SRE model
• Experience deploying & operating SaaS and/or IaaS at scale
• Experience deploying agentic AI to replace rote tasks in SRE, networking, & SaaS diagnostics
• Experience with IT operations, supply chain, and data center operations at scale
• LAN networking deployment & operation experience

Ideal Candidate

• SRE or DevOps leader who has built and scaled a team of 300+ engineers, with at least 50% recruited and developed directly under your leadership
• Infrastructure-focused executive with a track record of large scale deployment with tight SLAs
• CTO from a scaled, high-uptime SaaS who has owned the full technical stack
• Actively using AI in current SRE and operational activities