OpenAI hires senior engineers from Tesla, xAI, and Meta to strengthen its infrastructure team

The challenge now is to scale hardware and staff amidst the AI talent war.

Four high-profile new hires reinforce the scaling team at a crucial stage for operational growth.

OpenAI has recently hired four key figures from leading tech and AI companies, including Tesla, Meta, and xAI. The announcement was initially shared internally by Greg Brockman, co-founder and head of the company’s scaling division. The new hires are David Lau (former VP of Software Engineering at Tesla), Uday Ruddarraju and Mike Dalton (both coming from xAI, also with experience at Robinhood), and Angela Fan, an AI researcher formerly at Meta. The operation has the stated goal of strengthening OpenAI’s technical infrastructure at a time when computational demand and efficiency requirements are growing exponentially.

The expertise each profile brings is aimed at strengthening different but interconnected capabilities.

David Lau led software development at Tesla for years and stated that he was attracted by OpenAI’s ambitious infrastructural vision, particularly the Stargate project, a joint initiative to build the next generation of AI supercomputers. Ruddarraju and Dalton, on the other hand, worked together on the construction of Colossus, xAI’s massive GPU infrastructure, and explained that they see OpenAI as a strategic continuation in terms of mission, oriented towards developing advanced AI aligned with human values. Angela Fan, finally, brings strong experience in AI research gained at Meta, where she contributed to the creation and training of large-scale language models, thus enriching the OpenAI team with critical applied machine learning skills.

Computing infrastructure is now a central pillar for competitiveness in generative AI.

This new wave of hires fits into the broader framework of strengthening OpenAI’s scaling team, responsible for the core components underpinning all research and production activities: backend hardware, distributed software systems, training pipelines, operational security, and data center architectures. The Stargate project, in particular, represents a strategic priority for OpenAI as it aims to build proprietary infrastructure capable of supporting the future loads of AGI, with computing power distributed on a global scale. Wired has defined this division as “where research meets reality,” emphasizing how the ability to scale is no longer a secondary factor but the necessary prerequisite for any credible technological evolution.

The competitive context is making the battle for top AI engineering talent increasingly intense.

OpenAI’s new hires come at a time of intensifying recruitment strategies by other major players, particularly Meta. The company led by Mark Zuckerberg has launched an aggressive talent acquisition campaign for its new internal division called Superintelligence Labs, offering very high compensation packages and dedicated computing resources. According to some sources, even sign-on bonuses worth tens of millions of dollars have been offered for the most strategic profiles. In the face of this pressure, OpenAI is also reviewing its retention and compensation packages, seeking to balance the attractiveness of the project with the long-term sustainability of its structure.

The hiring of former xAI engineers may further intensify existing tensions with Elon Musk.

Two of the new hires, Ruddarraju and Dalton, come directly from the xAI startup founded by Elon Musk, who in recent months has publicly voiced criticism and initiated legal actions against OpenAI over its transformation from a non-profit to a capped-profit company. The arrival of these profiles at OpenAI may fuel further tensions, even symbolically, in an environment already marked by legal disputes and divergences over AI governance. Although OpenAI has not issued official statements on the matter, many analysts interpret this move as a signal of independence and direct competitiveness with rival projects.

The operation is part of a broader strategy to reinforce infrastructure and consolidate leadership.

According to Joaquin Quiñonero Candela, OpenAI’s head of recruiting and a former Meta executive, the company is experiencing “unprecedented pressure” to grow in terms of human resources and computing capacity. The pace of expansion is accelerating: in less than two years, the staff has grown from a few hundred to thousands of employees, with an increasingly technical and infrastructural focus. The acquisition of these high-level profiles fits into this path and clearly represents an attempt to ensure OpenAI has the operational foundations needed to support the development of future models and the scalability of its entire architecture. It is therefore both a defensive and offensive move: on the one hand, it protects existing production capacity, and on the other, it prepares the ground for a potential leap forward toward more advanced and autonomous systems.

OpenAI is betting on infrastructure and talent to withstand the impact of the next generation of language models.

The simultaneous hiring of four senior figures with expertise in infrastructure and artificial intelligence indicates that OpenAI is fully aware of the need to consolidate its technical backbone. At a time when global competition is playing out not only on the models themselves but also on the ability to train and deploy them at scale, strengthening infrastructure becomes essential to remain relevant. OpenAI is therefore investing in what lies “underneath” the models visible to the public: GPU clusters, optimized pipelines, scalable software, backend engineering, and secure execution environments. In parallel, the growth of the human team becomes a key asset to maintain a competitive advantage over rivals such as Meta, xAI, Google, and Anthropic.

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