Extracellular vesicles (EVs) are cell-derived, membranous nanoparticles released by cells that facilitate the intercellular transfer of proteins and nucleic acids. This intrinsic delivery property of EVs, together with their low immunogenicity and potential for repeat administration, makes them promising delivery vehicles for novel therapeutics. The loading of cargo molecules into EVs constitutes one of the main challenges limiting clinical translation of EV-based therapies. Post-translational modification (PTM) of proteins with ubiquitin-like protein 3 (UBL3) has been previously implicated in the sorting of specific proteins into EVs. Initially, we assessed the utility of UBL3 as an EV-scaffold to enhance EV-loading of Cas9/sgRNA complexes by fusing Cas9 to UBL3 (to mimic the UBL3 PTM). This approach was shown to be successful in terms of the loading of Cas9 and sgRNA into the EVs, although no functional activity of the complexes was observed in the recipient cells after EV transfer. PTMs such as myristylation, ubiquitination, and prenylation have also been shown to play a role in EV-protein sorting. We were motivated to identify additional PTMs (and other sequence features) associated with EV loading that may be exploited for therapeutic purposes. To this end, we developed a novel bioinformatics analysis: integrated proteomics and feature annotation analysis (IPFA) that enabled the identification of EV-enriched annotated PTMs, protein motifs, and domains by combining protein feature annotations from UniProt with experimentally-observed EV-enriched proteins observed in proteomics data. This analysis identified several promising features, of which N-glycosylation was selected as the most promising PTM associated with EV protein enrichment. Specifically, the majority of N-glycosylation-annotated transmembrane proteins were EV-enriched, and nearly half of all EV-enriched transmembrane proteins were annotated as being N-glycosylated. Candidate protein features that were identified with the IPFA analysis were then experimentally assessed for their capacity to mediate functional cargo protein delivery. PTTG1P (Pituitary tumor-transforming gene 1 protein-interacting protein), a single-pass transmembrane protein with two annotated N-glycosyation sites, was selected as a putative EV-sorting scaffold. PTTG1IP was found to be highly enriched in EVs in an N-glycosylation dependent manner. Highly efficient functional delivery of Cre recombinase to reporter cells and mouse xenograft tumors was accomplished using PTTG1IP as an EV scaffold. Indeed, cargo molecules fused to PTTG1IP scaffolds were successfully delivered to recipient cell cultures with improved efficiency relative to the commonly used CD63-based scaffold. The PTTG1IP platform was further utilized for successful Cas9 and Cas9/sgRNA complex delivery to reporter cells. Several PTTG1IP variants with improved properties for therapeutic delivery were also developed (i.e., reduced size, enhanced loading potential, and enhanced intrinsic cleavage for cargo release), demonstrating the potential for further engineering PTTG1IP beyond its native human amino acid sequence. To achieve functional delivery, PTTG1IP-cargo fusion constructs were designed to include self-cleaving sequences (i.e., an intein from Mycobacterium tuberculosis or an intrinsic cleavage sequence derived from PTTG1IP itself) to facilitate cargo release from the EV scaffold. Furthermore, co-expression of the fusogenic protein VSVG (vesicular stomatitis virus glycoprotein) was utilized to enhance cellular uptake and promote endosomal escape. In summary, PTTG1IP was identified as a suitable EV-loading scaffold using IPFA, and its ability to efficiently package and deliver protein and protein/RNA complexes was demonstrated in both cell cultures and in vivo. Notably, PTTG1IP EV-sorting was shown to be dependent on its N-glycosylation PTMs, providing a validation of the robustness of the IPFA approach. The PTTG1IP-based platform offers significant advantages over other EV-loading strategies, (such as favorable membrane topology, the potential for further engineering, and functional delivery capability), which will enable the development of improved EV-based therapeutics.