RNA-guided endonucleases (RGENs) have invigorated the field of site-specific nucleases. The success of Streptococcus pyogenes Cas9 (SpCas9) has led to the discovery of several other CRISPR-associated RGENs. As more RGENs become available, it will be necessary to refine their activity before they can be translated into the clinic. With this in mind, we sought to demonstrate how deep mutational scanning (DMS) could provide details about important functional regions in SpCas9 and speed engineering efforts. Consequently, we developed a nuclease screening platform which could distinguish active Cas9 mutants. We screened a library of 1.9 × 107 with over 8500 possible non-synonymous mutations and inferred the effects of each mutation using DMS. We demonstrate that the RuvC and HNH domains are the least tolerant regions to mutation. In contrast, the Rec2 and PI domains tolerate mutation better than other regions. The mutation information defined in this work provides a foundation for further SpCas9 engineering. Together, our results demonstrate how DMS can be a powerful tool to uncover features important to RGEN function. Application of this approach to emerging RGENs should enhance their engineering and optimization for therapeutic and other applications.