Physical AI company RLWRLD (RLWRLD) said on Tuesday it has hired Karthik Krishnamurthy (카르틱 크리슈나무르티), formerly of Amazon Web Services (AWS), as a founding member and leader overseeing global market entry and strategic partnerships.

Krishnamurthy will join RLWRLD’s U.S. leadership team and lead commercial expansion across the United States and Europe.

Before joining RLWRLD, Krishnamurthy worked at AWS for about 10 years and held roles including Global Head of Strategy & Business Development for the Automotive and Manufacturing Industry where he served as a trusted advisor to executives across global manufacturing companies such as Rivian, Toyota, Hyundai Motor, and Volkswagen, helping them navigate transformational initiatives.

Majoring in mechanical engineering, Krishnamurthy began his career on Toyota's production line, where he carried out projects involving production optimization, line automation, and new vehicle launches. After his Master’s degree in Manufacturing Systems Engineering from University of Wisconsin Madison, he was working at Ernst & Young US as an Advisory consultant for Manufacturing & Supply Chain before joining Amazon. An Executive MBA candidate at MIT Sloan School of Management, At RLWRLD, Krishnamurthy plans to work with global partners such as hyperscalers and hardware providers to build co-sell partnerships and distribution channels.

Krishnamurthy said, "Many customers and partners I met in the global field have already moved beyond simple curiosity and entered an execution stage, seeking business outcomes by deploying physical and industrial AI in real-world sites." He said some leading companies have already moved beyond proof-of-concept and are rapidly entering production deployments. "RLWRLD is building a robot foundation model at this major intersection, enabling robots to perform dexterous manipulation with human-like five-finger hands," he said. "I was deeply impressed by the performance shown by the RLDX-1 model in real industrial settings, and I will work with global partners to scale this technology in the market and deliver outcomes that customers can apply in real production environments," he said.