Anthropic hires Google TPU veteran Amir Salek for its own chip push

Anthropic has hired Amir Salek, the engineer who founded Google's custom-chip program and ran its Tensor Processing Unit business, to lead its in-house silicon effort as the Claude maker builds its own hardware. Salek, who delivered the first seven generations of Google's TPUs before leaving in 2022, will join Anthropic's compute team and report to its head, James Bradbury, according to a Bloomberg report published August 21. The hire signals Anthropic's push to reduce reliance on external chip suppliers like Nvidia, Google, and Amazon.

Anthropic hires Google TPU veteran Amir Salek for its own chip push Salek delivered Google's first seven TPU generations and joins James Bradbury's compute team as Anthropic assembles an in-house silicon operation. By Ryan Merket /author/ryan-merket · Published Primary source: X - Dina Bass https://x.com/dinabass/status/2090895643292082365 Why it matters AI labs increasingly compete on the cost and availability of compute. Salek gives Anthropic experience building a mature chip program while it remains a major customer of Nvidia, Google and Amazon. Anthropic has hired Amir Salek, the engineer who founded Google's custom-chip program and ran its Tensor Processing Unit business, as the Claude maker starts building an in-house silicon operation. Salek will join Anthropic's compute team and report to its head, James Bradbury, Anthropic confirmed in a Bloomberg report https://www.bloomberg.com/news/articles/2026-08-21/anthropic-taps-google-chip-veteran-as-part-of-push-into-hardware published on August 21st. Dina Bass @dinabass https://x.com/dinabass first summarized the hire in a post on X https://x.com/dinabass/status/2090895643292082365 . business-standard.com https://www.business-standard.com/technology/tech-news/anthropic-taps-google-chip-veteran-amir-salek-as-part-of-push-into-hardware-126082200097 1.html?utm source=openai Salek brings Anthropic the specific experience it needs: building a semiconductor organization inside a software and infrastructure business. He delivered the first seven generations of Google's TPUs before leaving in 2022, according to Bloomberg. Before Google, Salek founded and led Nvidia's system-on-a-chip design organization. He holds a doctorate in computer engineering and computer science from the University of Southern California. business-standard.com https://www.business-standard.com/technology/tech-news/anthropic-taps-google-chip-veteran-amir-salek-as-part-of-push-into-hardware-126082200097 1.html?utm source=openai The hire also brings Salek back to chip development after four years as an investor. He joined Cerberus Capital Management https://www.cerberus.com/media/amir-salek-joins-cerberus-as-senior-managing-director/ in March 2022 as a senior managing director and a partner at Tracker Ventures, a Cerberus platform investing in semiconductors, AI, edge computing, aerospace and other deep-technology sectors. cerberus.com https://www.cerberus.com/media/amir-salek-joins-cerberus-as-senior-managing-director/?utm source=openai Anthropic imports Google's chip-building playbook Anthropic confirmed earlier in August that it was recruiting a custom-silicon team, including engineers with experience taking semiconductor designs through production. Salek's arrival turns that hiring plan into a serious hardware effort. Google recruited him to establish a custom-chip capability and then deployed the resulting processors across its data centers and cloud business. Anthropic is asking him to help repeat that organizational feat for workloads built around Claude. arstechnica.com https://arstechnica.com/ai/2026/08/anthropic-confirms-plans-to-build-an-in-house-silicon-team/?utm source=openai A personnel move still leaves Anthropic several steps from deploying a processor. Designing a competitive AI accelerator requires architecture, verification, software, networking, packaging, manufacturing and years of iteration. Salek's record matters because it extends beyond a first chip: he oversaw repeated generations of silicon and the infrastructure required to operate them at data-center scale. Anthropic already works closer to the hardware than a typical software customer. In 2024, Anthropic said its engineers were writing low-level kernels for Amazon's Trainium accelerators, contributing to the AWS Neuron software stack and working with Amazon's Annapurna Labs on future chip generations. That work gives Anthropic experience optimizing Claude for specialized processors even before its own silicon reaches a data center. anthropic.com https://www.anthropic.com/news/anthropic-amazon-trainium?mod=article inline&utm source=openai Own chips, alongside everyone else's Anthropic's silicon effort does not amount to a clean break with its suppliers. Anthropic currently trains and runs Claude across Nvidia GPUs, Google TPUs and Amazon Trainium chips, describing the mix as a way to assign workloads to different hardware and reduce dependence on any single platform. Amazon remains Anthropic's primary cloud and training partner. anthropic.com https://www.anthropic.com/news/expanding-our-use-of-google-cloud-tpus-and-services?c=ordem&utm source=openai Those outside commitments are still expanding. In October 2025, Anthropic said it planned to use as many as one million Google TPUs, with well over a gigawatt of capacity expected during 2026. In April, Anthropic announced another agreement with Google and Broadcom for multiple gigawatts of next-generation TPU capacity beginning in 2027. Anthropic is therefore building an internal option while continuing to reserve enormous quantities of competing hardware. anthropic.com https://www.anthropic.com/news/expanding-our-use-of-google-cloud-tpus-and-services?c=ordem&utm source=openai That overlap is the strategy. Custom silicon could give Anthropic tighter control over supply, power consumption and the cost of serving Claude, while Nvidia, Google and Amazon provide the capacity Anthropic needs before an internal design is ready. Salek's hiring gives Anthropic an executive who has already built the most established alternative to Nvidia's general-purpose AI accelerators. The next test is whether Anthropic can turn that experience into a repeatable chip program rather than a single expensive experiment.