Working memory (WM) and decision making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal and prefrontal cortices (PPC and PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically-based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multi-regional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of fronto-parietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but in response to intervening distractors, PPC transiently encodes distractors, while PFC filters distractors and supports WM robustness. With regards to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function, and provide a framework for extension to multi-regional models.