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Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following a $200M Series B at a $1.4B valuation, the company is expanding teams to deliver mission-critical systems to allied forces.
As a Multi-Agent Mission Planning Engineer, you will design and implement Guidance, Navigation, and Control (GNC) algorithms that translate high-level mission goals into actionable guidance for autonomous robots and multi-agent systems. You will bridge cutting-edge research and field-ready autonomy, ensuring systems are both intelligent and predictable in live operations.
Key responsibilities include:
- Design algorithms that decompose high-level missions into structured, solvable guidance tasks for autonomous robots
- Develop and optimize mission and path-planning frameworks for autonomous systems
- Build scalable backend integrations for mission guidance and execution
- Run simulations and validation campaigns to assess autonomy consistency across diverse mission types
- Partner with AI/ML, backend, and product teams to ensure algorithms are efficient, testable, and deployable in real-time environments
The company values building technologies with real-world impact, pursuing excellence, setting ambitious goals, and tackling the hardest technical challenges. The role operates in a demanding environment where rigor, ownership, and execution are expected.
REQUIREMENTS:
- Education: Ph.D. or M.S. in Aerospace Engineering, Robotics, Applied Math, AI, or related field. Ph.D. in multi-agent systems or reinforcement learning is a strong plus.
- Experience designing and deploying mission- or path-planning algorithms in aerospace, defense, or robotics is a strong plus.
- Technical Skills: Strong coding proficiency in Python and C++. Deep understanding of autonomous decision-making, multi-agent coordination, and simulation frameworks.
- Mindset: Ability to move from research prototype to production-grade system.
- Commitment: 100% dedication to Harmattan AI's mission, vision, and ambitious growth plans.
