In this paper, we present ongoing research and development on a new parallel nonlinear programming solver, NLPAROPT, that is being developed by CU Aerospace with collaboration from the University of Illinois at Urbana-Champaign. The solution of a nonlinear program is at the heart of many optimal control software packages; the result of a control transcription of the optimal control problem, using both direct or indirect approaches. Hence nonlinear programming solvers play a pivotal role in astrodynamics applications. Currently, all available (commercial or open source) nonlinear programming solvers are inherently serial, with trivial parallelism or parallelism that has not necessary been designed holistically. With this paper, we present the overall architecture of NLPAROPT, discuss how structure from the dynamic optimization problem can be exploited and how users can best setup their problems from a robustness and numerical efficiency standpoint, and conclude with current results on spacecraft trajectory and control related optimization problems.