Structural engineers encounter significant challenges in planning, designing, and constructing safe buildings in hilly areas. Time history analysis of structure utilizing real-time ground motion data is the most accurate analysis for earthquake-resistant design. Currently, artificial intelligence models are being used to solve difficult real-world problems like earthquake analysis and structural design. The use of AI models can significantly reduce the time and effort required to efficiently create earthquake-resistant designs. Data generation was performed using the ETABS software, incorporating earthquake typical ground motions producing critical response to the typical structure. To develop an AI model for earthquake-resistant design, it is essential to consider key parameters of real earthquake ground motions, such as Peak Ground Acceleration, Peak Ground Velocity, Peak Ground Displacement, and the duration of the event and frequency of the ground motion which are in line with structural frequency. Additionally, building parameters, including maximum displacement, base shear, story drift and overturning moment were considered as essential factors as output in the AI model development process. The developed back propagation feed forward ANN model correctly predicts the design parameters of a typical target structure in hilly region which is computationally efficient. This meta-heuristic approach offers great research interest and possible applications in the design of earthquake-resistant structures due to its reduction in computational time and effort particularly for hilly region.