In this talk, we introduce a Reformulation-Linearization Technique-based open-source optimization software for solving polynomial programming problems (RLT-POS). We present algorithms and mechanisms that form the backbone of RLT-POS, including constraint filtering techniques, reduced RLT representations, semidefinite cuts, and bound-grid-factor constraints. We discuss the coordination between 1) constraint elimination via filtering techniques and reduced RLT representations, and 2) semidefinite cuts and bound-grid-factor constraints. We present computational results using instances from the literature as well as randomly generated problems to demonstrate the improvement over standard RLT.