To improve the strength, stiffness, and lightweight performance of the automotive roof front crossbeam, achieve a balance in materials and structure, and develop a design and optimization method for the carbon fiber composite front crossbeam, an improved particle swarm optimization-bacterial foraging optimization (PSO-BFO) hybrid algorithm and a multi-level layup optimization method were proposed. The carbon fiber composite roof front crossbeam was then designed using these approaches. A finite element model of the body-in-white was established and experimentally validated for accuracy, resulting in the finite element model of the front crossbeam before optimization. The performance of the front crossbeam under top compression, three-point bending, and compression conditions was simulated to determine the boundary conditions for layup optimization. Performance testing of the T700/WP-R2300 material was conducted to provide material parameters for the layup optimization. Through free-size optimization and size optimization, the shape and thickness of the carbon fiber composite front crossbeam layup were determined, and the layup sequence was optimized using the PSO-BFO hybrid optimization algorithm. After optimization, the weight of the front crossbeam is reduced by 45.47%, and the displacements under top compression, three-point bending, and compression conditions decrease by 43.64%, 29.58%, and 28.61%, respectively. The stresses are reduced by 85%, 79.44%, and 75.03%, respectively, validating the effectiveness of the multi-level optimization method.