Aircraft design and manufacturing for next-generation transonic aircraft
Otto Aerospace is building a transonic aircraft designed for fuel efficiency and environmental performance, now ramping from low-rate to full-rate production at their facility. The tech stack is heavily weighted toward aerospace CAD, simulation, and systems engineering (CATIA, NX, MATLAB, Simulink, STAR-CCM+, JAMA, IBM DOORS) paired with enterprise resource planning (SAP S/4HANA, NetWeaver), signaling a mature manufacturing operation scaling from design validation into production. Hiring is almost entirely engineering-focused, with senior and mid-level roles dominating — a profile consistent with aircraft certification, supplier coordination, and production ramp challenges.
Otto Aerospace, founded in 2008 and headquartered in Fort Worth, Texas, develops a transonic aircraft optimized for operational efficiency and lower environmental impact. The company operates as a mature but lean aerospace manufacturer, moving through low-rate and full-rate production phases at their facility. Core work spans air vehicle integration, fuselage and empennage assembly, zonal reference model development, and flight-test vehicle builds of the Phantom 3500. With 51–200 employees and accelerating hiring velocity, Otto is scaling engineering capacity to address production ramp, supplier performance monitoring, regulatory certification, and the structural challenges inherent in aircraft development: fuel-burn reduction, schedule adherence, manufacturability, and reliability targets.
Otto uses CATIA, NX, MATLAB, Simulink, STAR-CCM+, Thermal Desktop, FEMAP, and AutoCAD Electrical for design and aerodynamic analysis, along with JAMA and IBM DOORS for requirements and configuration management.
Otto is manufacturing the Phantom 3500, a transonic aircraft designed for fuel efficiency and environmental performance, currently in low-rate and full-rate production phases.
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Otto Aerospace'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.