Large scale additive manufacturing (LSAM) of thermoplastics is a manufacturing process that is being adopted by industry for different manufacturing applications. However, LSAM faces multiple design challenges, including process dependence of the material properties resulting from fiber orientation, inter- and intra-bead voids, and design constraints from the deposition process. This work seeks to address these challenges via Analytical Target Cascading (ATC) multilevel optimization algorithm. Utilizing a process-informed simulation of a finite element model of a stiffened panel, ATC optimizes the process and material properties of the part coupled with the part design. The ATC optimization algorithm is demonstrated for mass minimization of a 3D-printed rectangular stiffened plate within a 4000 × 1000 × 500 mm3 design volume, with simple-support boundary conditions along all edges, loaded in uniaxial compression, and modeled using classical lamination theory. Results indicate mass reductions exceeding 20% compared to the baseline model, while keeping manufacturing feasible.