The construction domain in the Middle East region has experienced significant growth in recent years. In the United Arab Emirates (UAE), for instance, the number of newly constructed areas with mixed-use development buildings is increasing yearly. Given the region's harsh climatic conditions, characterized by an extremely hot climate, designing sustainable and energy-efficient buildings is crucial. Under these conditions, shading is a primary strategy. This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. It is focused on parametric design and optimization of window shading structures, either for retrofitting existing buildings or for new construction. Advanced tools are essential to achieve this goal, as they enable designers to incorporate various architectural features that enhance energy efficiency. The parametric structures are meant to increase the shaded parts by reducing the amount of solar radiation on building facades, reducing the amount of energy consumption for air conditioning and improving overall energy efficiency. The methodology follows the following steps: selection of the case study, weather analysis, modeling and simulation, parametrization process (maximize shaded area and reduce total solar radiation), results, and analysis. The modeling, simulation, and parametrization are completed using Rhino/GH. While the research focuses on a mid-rise building in Abu Dhabi as a case study, the approach can be applied more broadly to buildings in hot climates. Due to excessive solar radiation in arid climate regions, shading of fenestration is a primary focus. The findings show that the GA-based optimized shading system, based on the cumulative radiation, decreased the total radiation amount by 19% and reduced cooling energy use by 26.2% for the case study. This demonstrates that parametric design can contribute to more sustainable and energy-efficient architecture.