Former Google Energy Executive Joins Anthropic's New Energy Team

Apr 21, 2026
Sana Ouji, a longtime Google energy and data center executive, has joined Anthropic to help build its new energy team focused on scaling global data center operations.
Former Google Energy Executive Joins Anthropic's New Energy Team

Sana Ouji, a former Google executive specializing in data center energy strategy, has joined Anthropic's new energy team, reports Data Center Dynamics. Ouji spent more than six years at Google, most recently managing strategic investments and partnerships for data center energy.

At Anthropic, Ouji will collaborate with Ariel Horowitz and Tim Hughes on the company's first dedicated energy team. Horowitz joined in March after serving as deputy director of grid modernization at the US Department of Energy, and Hughes arrived in February from Stack Infrastructure, where he was chief development officer.

The team will work on developing and executing a global energy strategy to support Anthropic's expanding data center portfolio. The company recently committed to covering the full cost of grid upgrades required to connect new data centers in the United States.

Ouji joins several former Google employees now at Anthropic, including head of data center infrastructure Winnie Leung, data center construction lead Brett Rogers, and design lead Liwen Mao. Anthropic continues to recruit for additional data center roles as it increases its infrastructure footprint through partnerships with Microsoft, AWS, and Google.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief, Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.