Gnc Software Engineer

Anduril Anduril · Defense · Broomfield, CO · Mission Systems : Battlespace Awareness Engineering

This role is for a GNC Software Engineer at Anduril, a defense technology company. The engineer will work on an AI-powered operating system for command and control, focusing on path planning, route optimization, and multi-agent coordination for autonomous systems. Responsibilities include prototyping, deploying, and integrating state-of-the-art algorithms for real-time C2 systems, analyzing performance, and driving customer success through algorithm customization. The role requires strong programming skills in C/C++, Python, and Matlab, knowledge of path planning techniques, GNC, applied mathematics, and machine learning (especially reinforcement learning). The engineer will engineer robust systems for planning under uncertainty and multi-agent coordination in dynamic environments.

What you'd actually do

  1. 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.
  2. 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.
  3. Design and implement robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments.
  4. Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate planner behavior across diverse mission scenarios.
  5. Drive customer success by customizing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance.

Skills

Required

  • 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.

Nice to have

  • 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.

What the JD emphasized

  • mission-critical applications
  • real-world impact of our deployed solutions
  • customer success
  • mission-critical use cases
  • robust planners
  • dynamic, uncertain, and contested environments
  • high-fidelity simulations
  • rigorous statistical techniques
  • robust systems for planning under uncertainty
  • multi-agent coordination
  • complex, dynamic, contested environments
  • optimizing production systems

Other signals

  • AI-powered operating system
  • cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology
  • autonomous mission execution
  • path planning, trajectory optimization, and multi-agent coordination
  • autonomous tasking and routing services that orchestrate fleets of unmanned platforms
  • machine learning as applied to planning and decision-making, including reinforcement learning, learned heuristics, and behavior prediction