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Computational fluid dynamics (CFD) shape optimization technology is playing an increasingly significant role in the development of products that satisfy various demands, including trade-off relationships. It offers the possibility of designing or improving product shape with respect to a given cost function, subject to geometrical constraints. However, conventional CFD shape optimization technology that uses parametric shape modification has two following issues: (1) expensive computational cost to obtain the final shape, (2) performance variations of the obtained shape depends on the skill or experience of the designer who determined the locations to be modified. In this study, to resolve those problems, an efficient shape optimization technology was developed that uses the adjoint method to perform sensitivity analysis of a cost function on the design parameters. It is composed of a combination of topology optimization and surface geometry optimization.