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 RoleAs a Multi-Agents Mission Planning Engineer, you’ll design and implement the Guidance, Navigation, and Control algorithms that translate high-level mission goals into actionable guidance for autonomous robots and multi-agent systems. You’ll bridge cutting-edge research and field-ready autonomy, ensuring our systems are both intelligent and predictable in live operations.
ResponsibilitiesDesign 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 environment
Education: Ph.D. or M.S. in Aerospace Engineering, Robotics, Applied Math, AI, or related field. A PhD in the field of multi-agent systems or reinforcement learning is a huge plus.
Experience designing and deploying mission- or path-planning algorithms in aerospace, defense, or robotics is a huge plus
Technical Skills: Strong coding 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, ready to go the extra mile to ensure operational excellence.
We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.
Skills Required
- M.S. or Ph.D. in Aerospace Engineering, Robotics, Applied Math, AI, or related field
- Ph.D. in multi-agent systems or reinforcement learning
- Experience designing and deploying mission- or path-planning algorithms in aerospace, defense, or robotics
- Strong coding skills in Python and C++
- Deep understanding of autonomous decision-making, multi-agent coordination, and simulation frameworks
- Ability to move from research prototype to production-grade systems
- Full commitment to company mission and willingness to support operational excellence
Harmattan AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Harmattan AI and has not been reviewed or approved by Harmattan AI.
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Fair & Transparent Compensation — Pay ranges are publicly shown for multiple U.S. roles (e.g., $140k–$200k base) and appear broadly in line with late‑stage startup/defense‑tech expectations based on the postings cited.
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Equity Value & Accessibility — Equity is repeatedly referenced in several job postings as part of total compensation, which can increase upside potential at a recently funded, high‑valuation company.
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Strong & Reliable Incentives — Sign‑on bonuses are explicitly mentioned in a hiring post for candidates who can start quickly, indicating the use of cash incentives in at least some hiring situations.
Harmattan AI Insights
What We Do
Harmattan AI is rising as a next-generation defense prime, building the future of autonomous warfare. We leverage AI-driven autonomy, real-time intelligence, and conflict-ready production to deliver attritable systems and autonomous mission management software. Designed for the real-world needs of warfighters, our solutions enable faster deployment, sharper decision-making, and battlefield dominance.
