Over the past decade, ribosomally-synthesized and post-translationally modified peptides (RiPPs) have emerged as both therapeutically-relevant and engineerable, two traits previously unobserved together in a natural product class. Their biosynthesis is modular: a precursor peptide recruits enzymes that bind one region of the peptide and modify another. This separation of substrate recognition from catalysis allows modifying enzymes to be both highly specific for their peptide and permissive of diverse sequences at the modification site. After modification, the molecules are chemically diverse, sometimes not appearing peptidic at all, and can exhibit picomolar activity for their biological targets in nature. As medium-sized constrained molecules, they also have exciting applications in drug discovery as protein-protein interaction inhibitors, a modality that is currently out of reach of small molecules and antibodies. Despite the therapeutic potential of these molecules, their development has been hampered by a lack of genetic tools and standardized protocols to express, modify, and engineer peptides. Simple peptide expression in a heterologous host, outside the context of a native pathway, is complicated by peptide degradation and solubility, while existing bulky stabilization tags interfere with analytics. As such, efforts to engineer biosynthesis of new RiPPs have been ad hoc, with no formalization of methods to elucidate enzyme-substrate specificities or engineer multi-enzyme pathways. To address this, I utilize a peptide stabilization tag that is small enough for peptides to be analyzed without tag removal, showing both stabilization of diverse peptides and compatibility with their respective modifying enzymes. I then use the stabilization tag and its established expression/purification pipeline to characterize substrate constraints of 9 enzymes in order to engineer biosynthesis of new-to-nature “hybrid peptides”. Collectively, these standardized expression tools, expression conditions, and engineering principles form an enabling platform for future RiPP discovery and engineering.Ph.D