PaperAbstract. Workflows applications are becoming increasingly important to support scientific discovery. That is leading to a proliferation of workflow management systems and, thus, to a fragmented software ecosystem. Integration among existing workflow tools can improve development efficiency and, ultimately, increase the sustainability of scientific workflow software. We describe our experience with integrating RADICAL-Pilot (RP) and Parsl as a way to enable users to develop and execute workflow applications with heterogeneous tasks on heterogeneous high performance computing resources. We describe our approach to the integration of the two systems and detail the development of RPEX, a Parsl executor which uses RP as its workload manager. We develop a RP executor that executes heterogeneous MPI Python functions on CPU cores and GPUs. We measure the weak and strong scaling of RPEX, RP and Parsl when providing new capabilities to two paradigmatic use cases: Colmena and Ice Wedge Polygons.