Here, we present OpenFF BespokeFit, an open-source, automated python package for bespoke FF parameter fitting. This first version of BespokeFit specifically aims to derive bespoke torsion parameters for individual molecules but we plan to extend it to additional FF terms in future. BespokeFit is designed for compatibility with the SMIRKS Native Open Force Field (SMIRNOFF) format, hence it uniquely provides users with the opportunity to re-fit torsion parameters, using robust methods that are consistent with the base OpenFF parametrization philosophy. We make use of the unified quantum chemistry (QC) program executor QCEngine to provide simple, resource-agnostic access to a wide range of quantum, semi-empirical and machine learning based reference data, which can be generated on-the-fly. Furthermore, we introduce OpenFF QCSubmit as an open-source tool for curating, submitting and retrieving large QM reference datasets from QCArchive to aid large-scale FF parameter fitting. We demonstrate the utility and easeof-use of the BespokeFit/QCSubmit interface by deriving bespoke torsion parameters for a large dataset of 671 QM torsion scans derived from fragments of drug-like molecules. We further demonstrate the ability of BespokeFit to construct FFs for a congeneric series of inhibitors of the TYK2 protein, and benchmark the accuracy of the resulting FFs by computing protein-ligand binding free energies and comparing against experimental data.