The drone industry has been experiencing considerable growth, with market demands quickly evolving, which put great pressure on manufacturers. To address this challenge, the usage of flexible, efficient and accurate numerical tools are paramount to speed up to design process. The methodology put in place by Tekever for the aerodynamic design of its next generation fixed-wing drones is outlined and demonstrated with some study cases. The underlying aerodynamic shape optimization framework is composed of five main modules: surface and volume grid generators, free-form deformation (FFD) technique for shape control, high-fidelity Reynolds-averaged Navier--Stokes flow solver, companion adjoint solver for sensitivity analysis, and gradient-based optimizer. Three application problems are presented and discussed, including the design of (i) fairings for protruding parts, (ii) nacelle of on-wing piston-engine, and (iii) winglets. The fairing and nacelle problems consisted of finding the minimum drag shapes covering the payload protruding from the fuselage or the piston-engine mounted on the wing, respectively, where a careful identification of the encapsulated 3-D body geometry and placement in the aircraft, as well as the definition of the fuselage or wing surface region extension, were necessary. The winglet problem implied a parametrization of its geometry that mapped the degrees-of-freedom of the FFD control points to meaningful engineering parameters, such as winglet cant and sweep angles, length and taper ratio. All cases presented a significant improvement over the baseline aircraft performance, ranging from a few percent to double digit reduction in aerodynamic drag. Also relevant, the use of large scale computing facilities made overnight turn around possible for every design problem tackled, allowing for the aircraft designers to quickly respond to customer demands as intended.