We address the ongoing development of a dynamic soaring (DS) capable unmanned aerial vehicle (UAV) platform optimized for minimal power consumption. This project has been funded by the Embry-Riddle Office of Undergraduate Research through the Ignite program. Dynamic soaring is a bio-inspired flight maneuver in which energy is extracted from the wind shear layer by flying through regions of varying wind speed. The objective of our project is to design an autonomous dynamic soaring flight controller and perform DS with a real-world UAV. Development of this project can be divided into three sub-categories: (1) the UAV platform, (2) flight simulations, and (3) the flight controller. The UAV platform is an FMS Fox Aerobatic Glider, a high aspect-ratio glider with a nose-mounted engine. A flight control system has been crafted to allow us to integrate our DS autopilot. In previous works we have created a 6-degree-of-freedom (6DoF) flight simulation environment in MATLAB and Simulink to develop and test DS flight controllers. The simulator can be adapted to integrate our current UAV by building a variable-fidelity aerodynamic model using computational fluid dynamics (CFD). Finally, we are developing a robust reinforcement-learning (RL) trained artificial intelligence (AI) that will optimize the path of the UAV to minimize power consumption. RL is performed in the simulator and the AI will be deployed on the UAV when complete. This presentation will discuss current progress as well as address challenges we face in the completion of our goals.