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Air Space Intelligence (ASI) is modernizing America's air traffic control system with 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 Simulation Software Engineer on the Civil Aviation team, you will create software simulators to model the behavior of the entire National Airspace System, including aircraft trajectories, weather, ATC and pilot behavior, and more. You will leverage your knowledge of discrete-time simulation, physics, statistics, and algorithms to design and implement simulation infrastructure and models. This role demands exceptional precision, resilience, and reliability to support the safety and efficiency of the national airspace.
You will work across teams in a mission-critical environment, collaborating with colleagues to validate and tune algorithm performance using Monte Carlo analysis and other techniques. You will leverage modern LLM tools 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 ability to timely obtain all required authorizations for contemplated job duties, including U.S. immigration status and location restrictions on some contracts.
QUALIFICATIONS & REQUIREMENTS:
- Experience building infrastructure for discrete-time simulations
- Experience implementing physics-based models in discrete-time simulations
- Experience designing algorithms for mission-critical applications
- 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
