GNC Software Engineer

About The Role

The Battelspace Awareness Command and Control Software team at Anduril Industries specializes in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. We are seeking highly talented technologists to join our mission and redefine the future of defense technology.

Key Responsibilities

• Define and influence the direction of a small team within the Command and Control Software organization, leveraging subject-matter expertise in path planning and route optimization.
• Prototype and deploy state-of-the-art algorithms for global and local path planning, trajectory optimization, and multi-agent coordination within command and control systems.
• Develop high-performance software for real-time C2 systems, ranging from operator-facing mission planning tools to autonomous tasking and routing services that orchestrate fleets of unmanned platforms.
• Design and implement robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments.
• Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate planner behavior across diverse mission scenarios.
• Drive customer success by customizing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance.
• Integrate path planning technologies into the broader command and control software stack and development lifecycle, from requirements definition through testing and optimization.
• Translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues, operators, and end-users.

Requirements & Tech Stack

• Proficiency in algorithm design, software development, and mathematical modeling with programming expertise in C/C++, Python, and Matlab.
• Strong knowledge of path planning techniques, such as graph-based search (A*, D Lite*), sampling-based planners (RRT, *RRT **, PRM), and lattice or grid-based planners.
• Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6-DoF simulation, intercept analysis).
• Solid understanding of applied mathematics, including linear algebra, optimization, computational geometry, and graph theory.
• Knowledge of vehicle dynamics, kinematic constraints, and control theory as applied to autonomous ground, air, or maritime platforms tasked through C2 systems.
• Familiarity with map representations, terrain reasoning, and the efficient handling of large-scale geospatial and environmental data within distributed C2 architectures.
• Background in machine learning as applied to planning and decision-making, including reinforcement learning, learned heuristics, and behavior prediction.
• Ability to engineer robust systems for planning under uncertainty, multi-agent coordination, and operation in complex, dynamic, contested environments.
• Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems.
• Eligible to obtain and maintain an active U.S. Top Secret security clearance.

Transcripts are requested as part of the early application process to understand academic background and how coursework supports critical skills.

Qualifications

• Proficiency in algorithm design, software development, and mathematical modeling.
• Programming expertise in C/C++, Python, and Matlab.
• Strong knowledge of path planning techniques.
• Demonstrated experience in GNC, trajectory optimization, and/or predictive model development.
• Solid understanding of applied mathematics.
• Knowledge of vehicle dynamics, kinematic constraints, and control theory.
• Familiarity with map representations and terrain reasoning.
• Background in machine learning for planning and decision-making.
• Ability to engineer robust systems for planning under uncertainty and multi-agent coordination.
• Ability to work across development lifecycles.