Wire arc additive manufacturing (WAAM) is attributed to higher material deposition rates and medium to large build volumes. Integration of multi-axis (more than three) material deposition kinematics in WAAM can bring a paradigm shift in the metal additive manufacturing industry. The material build-up mechanism employing directed energy deposition results in localized melting and solidification of feeding wire making the fabricated structure inherently prone to deposition defects such as dimensional distortion, residual stresses, solidification cracking, and porosity. Optimization of welding process parameters can improve cracking and porosity behavior. However, the problem of distortion is inevitable, and current mitigation strategies rely on post-processing or symmetric material deposition; while the former decreases the effectiveness of WAAM and increases costs, the latter could only be implemented for specific parts. Tackling this problem with the help of computational design tools is a recent approach, and Fabrication Sequence Optimization dictating material deposition is numerically predicted to limit the extent of the distortion effectively compared to conventional planar horizontal deposition; however, this still lacks experimental validation. This research presents a series of fabrication experiments using Al5356 Aluminum-magnesium alloy wire in a 6-axis robotic WAAM setup in two parts: (1) Process parameters identification for optimal bead characteristics for Al5356 wire, (2) Fabrication of single-bead multi-layered thin-walled shell structures using planar and optimized material deposition. A digital image correlation-based non-contact in-situ distortion measurement setup is constructed to analyze strain development during fabrication process and 3D scanning of fabricated structures is performed to estimate dimensional deviation. The experimental findings revealed an improvement in geometrical formation and a qualitative indication of distortion minimization with an optimized fabrication sequence.