Complex engineering design optimization often requires multiple executions of computationally expensive simulation tools such as those based on Computational Fluid Dynamics (CFD). Some CFD simulations can take several hours to complete, thus potentially making the design optimization task infeasible. In this paper, a combination of two powerful methodologies is presented that has the potential of reducing the engineering time required for CFD based design by more than 90%. The first methodology, termed as Parallel Parameterized CFD (PPCFD) allows for speeding up multiple CFD runs to explore a given design space very efficiently. The second approach is Approximation Assisted Optimization (AAO). AAO techniques are used to reduce the time and effort involved in conducting optimization with computationally expensive simulations.The PPCFD methodology needs to be tailored or customized for an individual geometry of interest. On the other hand, the AAO method discussed in the paper is generic and can be applied to any optimization problem. The combination of these two techniques can significantly reduce the engineering time and the computation time, thereby reducing the overall time to market for a given product. Several examples are presented that highlight the strengths of this approach. These include optimization of different types of heat exchangers such as microchannels used in electronic cooling, A-Type air-cooled heat exchanger, and Chevron plate heat exchanger.