GNC Software Engineer (Civil Aviation)

Description

About ASI

ASI is the frontier AI company that dynamically orchestrates critical infrastructure and defense assets, across air traffic control, energy, logistics, and combat operations. ASI's systems simulate physical operations, hours, days, and weeks ahead, so the people running air traffic control, the electric grid, and military operations can catch problems early and act before they spread. ASI is powering vital infrastructure for customers like United Airlines, National Grid, the Federal Aviation Administration, Delta Air Lines and the Department of War. ASI is headquartered in Boston with offices in Washington, DC, Denver, and Europe, and is backed by leading investors, including Andreessen Horowitz, Citadel Securities, and Spark Capital.

About the Civil Aviation Team

We are modernizing America’s air traffic control system on an accelerated timeline, 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. Our 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. This mission-critical work demands exceptional precision, resilience, and reliability to support the safety and efficiency of the national airspace.

Responsibilities

• As a Guidance, Navigation, and Control (GNC) Software Engineer on the Civil Aviation team, you will design algorithms help track and plan trajectories for thousands of aircraft operating in the National Airspace System (NAS). You will use your knowledge of state estimation, physics, aircraft design, optimization, and algorithms to design, analyze, and implement software to help monitor and control one the world’s most complicated airspaces in real time.
• What We Value
• 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
• Experience with modern programming languages such as Rust and Python
• Strong collaboration skills and comfort working across teams in a mission-critical environment.
• Proficient in leveraging modern LLM tools to accelerate development workflows and enhance code quality.