Engineering Roles

You’ll implement autonomy algorithms as software that meets hard timing guarantees. Model-predictive controllers, reinforcement-learning policies, and hybrid neuro-symbolic architectures arrive from researchers as prototypes; you turn them into C++ that runs inside a real time control loop. You’ll integrate with C2 systems and open-architecture standards so autonomy composes with the rest of the mission rather than standing apart from it, and you’ll build the message plumbing; protocols, ROS interfaces, and the coordination layers that enable multiple platforms to behave as a swarm rather than a collection.
The simulation-to-reality gap is where much of the work lives. You’ll build and maintain the simulation environments the algorithms are developed against, then discover what the simulation got wrong when the code encounters reality: sensor noise the model didn’t have, latency the loop didn’t budget for, a failure mode nobody wrote a case for. You’ll instrument extensively, use static analysis to catch what testing on hardware is too expensive to catch, and iterate between sim and flight. Some of your code runs on embedded processors on the platform; some runs on the ground in the mission planning stack.