Hydrogen-powered heavy-lift drones and autonomous UAS for defense missions
Heven AeroTech builds hydrogen-powered heavy-lift unmanned aircraft for defense, commercial and public safety customers. Its stack pairs edge AI tooling (NVIDIA Jetson, TensorRT, ONNX, ROS) with PLM systems (Windchill, Teamcenter) and CFD suites, pointing to onboard autonomy work alongside a push from prototype to repeatable production. Accelerating, engineering-heavy hiring, plus ITAR, CMMC and Army acquisition pressures, signals a company scaling into defense programs.
Notable leadership hires: Business Development Director
Heven AeroTech is a privately held aerospace technology company headquartered in Sterling, Virginia, with 51–200 employees. It designs, engineers and manufactures autonomous unmanned aerial systems, including hydrogen-powered heavy-lift drones. The company serves defense, commercial and public safety missions, with stated focus areas including precision agriculture and defense solutions. Engineering, manufacturing and flight testing are run in-house, and hiring is concentrated in the United States.
Heven AeroTech uses Python, C++, PyTorch, TensorFlow, ROS, NVIDIA Jetson and TensorRT for autonomy, plus SolidWorks, CATIA, NX, Windchill, Teamcenter, ANSYS Fluent and STAR-CCM+ for engineering and PLM.
Yes. Hiring is accelerating and engineering is the largest focus, with additional roles in operations, sales, manufacturing and procurement, all in the United States, including a Business Development Director.
Current work includes scalable manufacturing of hydrogen systems, sustainment-ready military UAS, mission-level autonomous behaviors, perception integration, and flight test planning.
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Heven AeroTech's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.