EU remote
Automated Testing Module Lead
About this role
About Us Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges.
We operate in a demanding environment where rigor, ownership, and execution are expected. About the Role As Automated Testing Module Lead, you take ownership of how Harmattan validates its autonomy and flight-software stack. Today, our software is validated mostly against real hardware, a process that consumes airframes, range time, and crew while sampling only a handful of nominal trajectories. The cases we actually build for, such as degraded GNSS, sensor dropout, electronic warfare, and multi-agent situations, are rarely reached economically that way.
Your mission is to establish the scenario library, execution strategy, and interface bricks to turn our existing simulation platform into a fast, reliable, and continuous validation engine. This is a senior, hands-on technical leadership role. You inherit an active team of four engineers across Paris and Lausanne, with a target of around eight by mid-2027. Beyond leading the team, you become the technical authority on our scenario-based testing: defining what runs across SITL, HITL, and CI, holding critical technical boundaries with adjacent teams, and bridging the gap between simulation fidelity and real flight data.
What You Will Do Team Leadership & Strategy: Take over, structure, and give a clear mandate to our existing team of four engineers, while building the case and the roadmap to scale the module to around eight by mid-2027. Scenario & Simulation Engineering: Drive the design of a versioned scenario library covering nominal, edge, off-nominal, and contested flight conditions, expanding into Monte Carlo and multi-agent testing, and bring a team with no prior simulation experience up that curve.