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Air Space Intelligence (ASI) is modernizing America's air traffic control system, delivering mission-critical technology that powers decision-making across aviation, defense, energy, and critical infrastructure. Backed by top-tier investors including Andreessen Horowitz, Spark Capital, and Renegade Partners, ASI compresses days of analysis into seconds of action.
The Civil Aviation team is tackling one of the world's most complex real-time optimization challenges: safely coordinating tens of thousands of daily flights in a dynamic, safety-critical environment. The team is building next-generation trajectory prediction and decision-support systems while preparing the airspace for emerging technologies like commercial space operations and advanced air mobility.
As a Guidance, Navigation, and Control (GNC) Software Engineer, you will design algorithms to track and plan trajectories for thousands of aircraft operating in the National Airspace System (NAS). You will apply knowledge of state estimation, physics, aircraft design, optimization, and algorithms to design, analyze, and implement software that monitors and controls one of the world's most complicated airspaces in real time. This is mission-critical work demanding exceptional precision, resilience, and reliability to support the safety and efficiency of the national airspace.
The role emphasizes collaboration across teams in a mission-critical environment and leveraging modern tools, including LLMs, to accelerate development workflows and enhance code quality.
IMPORTANT: ASI works with export-controlled technology and restricted U.S. Government data. Employment offers are contingent on the ability to timely obtain all required authorizations for contemplated job duties, including potential U.S. immigration status and location restrictions on certain contracts.
QUALIFICATIONS & REQUIREMENTS:
- Experience designing algorithms for mission-critical applications
- Expertise in core GNC domains, including state estimation and algorithm design
- Experience with Monte Carlo analysis as a means to validate and tune algorithm performance
- Domain experience in aviation or related fields where physical systems are modeled and controlled
- Proficiency with modern programming languages such as Rust and Python
- Strong collaboration skills and comfort working across teams in a mission-critical environment
- Proficiency in leveraging modern LLM tools to accelerate development workflows and enhance code quality
