The increasing demand for automation in construction necessitates robotic solutions that can address labor shortages, safety concerns, and efficiency challenges. Humanoid robots, with their human-like form factor, are particularly well-suited for traversing and operating in human-centric construction environments. We presented an integrated humanoid robotic framework designed for robust locomotion and payload transportation across diverse construction surfaces. Our system combines dynamic bipedal walking with effective payload-carrying mechanisms, enabling seamless transitions between surfaces such as flat ground, ramps, stairs, narrow beams, random obstacles, and irregular trenches while carrying loads of up to 9 lb. We employed a unified training approach using reinforcement learning to achieve stable locomotion and real-time adaptation of walking styles based on the surface conditions. Experimental results demonstrate that our framework enables continuous locomotion at speeds up to 0.42 m/s across complex construction environments, showcasing the potential of humanoid robots in construction logistics.