Shape optimization is a powerful method to design efficient aerodynamic shapes for aircraft and engine configurations at a limited cost. However, performing an optimization on “real-world” problems, including industrial tools and processes, remains challenging. In this paper, an original approach is presented, aiming at integrating expert knowledge and reducing the dimension of the optimization search space. Thanks to this method, it becomes possible to perform gradient-free or gradient-based optimization with an industrial design workflow comprising CAD. When applied to a nozzle shape optimization problem, this approach leads to encouraging performance improvements in both inviscid and viscous cases, for a given level of fuel consumption. Moreover, the reduced number of parameters enables the use of response surfaces and a better understanding of the design space.