Software Engineer, GNC

What you'll do

• Prototype and deploy state-of-the-art algorithms for global/local path planning and multi-agent coordination.
• Develop real-time path planning capabilities that adapt to changing mission conditions and threats.
• Build high-performance software for C2 systems using asynchronous programming and concurrency in resource-constrained environments.
• Implement robust search algorithms and decision-making systems to generate safe routes in contested environments.
• Analyze system performance using high-fidelity simulations and statistical techniques to validate planner behavior.
• Develop software for mission-critical use cases including collaborative autonomy, asset routing, and obstacle avoidance.
• Integrate path planning technologies into the broader command and control software stack across the development lifecycle.
• Translate technical progress into actionable insights for stakeholders, operators, and end-users.

What we're looking for

• 3+ years of experience in algorithm design, software development, and mathematical modeling using C/C++ or Rust.
• Strong knowledge of path planning techniques including graph-based search, sampling-based planners, and real-time replanning.
• Demonstrated experience in guidance, navigation, and control (GNC), trajectory optimization, and predictive models for vehicle dynamics.
• Solid understanding of applied mathematics including linear algebra, optimization, computational geometry, and graph theory.
• Knowledge of vehicle dynamics, kinematic constraints, and control theory for autonomous ground, air, or maritime platforms.
• Familiarity with map representations, terrain reasoning, state estimation, and large-scale geospatial data handling.
• Exposure to machine learning as applied to planning and decision-making, including reinforcement learning and behavior prediction.
• Eligible to obtain and maintain an active U.S. Secret security clearance.
• Experience with Rust for high-performance, safety-critical software (preferred).
• Exposure to mixed greenfield/brownfield codebases, including extending existing production stacks (preferred).