This role has closed. Stark has taken the posting down.
hirly last saw it live on 27 September 2026. See similar open roles below, or browse all jobs in Munich.
Stark
Senior AI & Flight Dynamics Integration Engineer (All genders)
Munich
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hirly's read of this role
- Seniority
- Senior
- Country
- DE
- Work mode
- On-site / unstated
- First seen by hirly
- 27 Sept 2026
Derived automatically from the posting.
the posting
About Us STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop, and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective — providing operators with a decisive edge in contested environments.
We are focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe, today.
About the team You will join our Open Source Aero Simulation team, dedicated to building and scaling next-generation autonomous flight systems. We focus on developing, validating, and implementing end-to-end aerodynamic and flight dynamics workflows built primarily on open-source tools and simulation frameworks. By integrating cutting-edge AI agents with open-source platforms, we accelerate rapid prototyping, multidisciplinary design optimization, and mission-critical aircraft analysis. We operate in an agile, hands-on environment where open engineering and cross-disciplinary innovation drive everything we build.
Your mission As a Senior AI & Flight Dynamics Integration Engineer, you will own and develop an AI-driven autonomous aircraft design and optimization workflow at STARK. You will integrate LLMs and AI agents with aerodynamics, CFD, flight dynamics, and multidisciplinary simulation tools to accelerate rapid prototyping and aircraft development. Your mission is to automate complex engineering decision-making loops and deliver highly performant, software-defined flight platforms.
- Responsibilities
- Develop LLM and AI Agent-based engineering workflows to interpret aircraft requirements and support iterative design decisions.
Automate parametric aircraft geometry using OpenVSP, Python, and STEP-based CAD workflows.
Integrate Flow5 (VLM / Panel Methods) and OpenFOAM CFD to build aerodynamic databases including C_L, C_D, C_m, C_p, and stability derivatives.
Develop 6-DoF flight dynamics and flight mechanics models, including trim, stability, control authority, propulsion, and aircraft performance calculations.
Integrate aircraft KPIs such as take-off/landing speed and distance, range, endurance, rate of climb, and efficiency into an automated optimization loop.
Drive multidisciplinary design optimization (MDO) frameworks to rapidly evaluate aircraft trade-offs.
Collaborate with systems and software teams to validate dynamic models against simulation and flight test data.
- Qualifications
- Minimum 5+ years of relevant professional experience in engineering automation, aerodynamics, or flight systems.
Strong background in Flight Dynamics, Aerodynamics, and Stability & Control.
Demonstrated experience with Python and engineering workflow automation.
Hands-on experience with OpenFOAM, VLM/Panel methods, or OpenMDAO.
Degree in Aerospace, Aeronautical, Systems, Computer Engineering, or a related field.
- Nice to have
- Direct knowledge and experience with OpenVSP and Flow5.
Hands-on experience integrating LLM APIs, AI Agents, and modern MDO tools.
Experience in unmanned aerial systems (UAS) or rapid-prototyping defence environments.
If you're interested in building the future of European Defence with us, and you see yourself reflected on the description above, please send us your CV in English . We´re looking forward to meeting you!
The proliferation of low-cost UAS has fundamentally changed the threat landscape, and STARK is building the system that counters it. As Product Manager for our C-UAS C2 software suite, you will own the vision and execution of the central intelligence layer connecting sensor networks to effector tasking. Your mandate is clear: compress the DTIM loop, reduce operator cognitive load, and ship a product that works when lives depend on it.
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