Location: Los Angeles, CA Team: Engineering Reports to: Chief Engineer
The US needs 1.5 terawatts of new power by 2035. AI has scaled beyond our ability to build power, and the existing power supply chain is the bottleneck. You cannot buy a new gas turbine until 2030: order books at GE, Siemens, and Mitsubishi stretch past 2030. Turbine prices have nearly tripled since 2019. The future demands a new kind of hardware company, building a new kind of turbine. That’s Stone.
We are America’s Turbine Company, designing, fabricating, and deploying turbines for a $200B+ market that’s tripling by the early 2030s. We are building our own factories. We are delivering our own natural gas, steam, and advanced turbines. And we are doing it with an AI stack built specifically for hardware.
Natural gas turbines are the first leaf on a multi-decade tech tree. The same physics kernel, the same factory, and the same team will deliver nuclear turbines, geothermal turbines, heat recovery systems, and propulsion engines. Nat gas is how we get going. Nuclear (on and off planet) is how we become a generational company.
This is a founding team role: one of the first engineers who will define the culture, pace, and competency bar at Stone. Every founding employee has shipped hardware at scale, and we keep doing it for the love of the game. The data is only half the moat; the ability to turn our designs into atoms rapidly closes the loop. In power generation, we are both Nvidia and TSMC.
Stone Power is scaling fast, and AI is at the core of how we design, simulate, manufacture, and operate our hardware. This role will own the integration of AI tools and workflows across our engineering organization, starting with simulation and analysis and expanding into other engineering activities later. You'll work directly with our hardware engineering teams to identify where AI can compress design cycles, improve analysis fidelity, and unlock new capability, while ensuring our proprietary IP stays secure and in-house.
This is not a pure software or ML research role. It's for an engineer with deep simulation/analysis roots who wants to go all-in on AI as the next chapter of their career.