Foodborne bacterial outbreaks caused by Shiga-toxigenic E. coli (STEC) continue to place a burden on public health systems in developed countries. The STEC family of pathogens is biochemically diverse and current microbiological methods for detecting STEC may be encumbered by lack of a universal selective enrichment method. Here we build upon a previously described method where genomic antimicrobial resistance (AMR) prediction tools are used to inform a selection of custom enrichment techniques for recovery of a target STEC strain from ground beef, and demonstrate the broader applicability of custom selective enrichment using recovery of five unique STEC strains from additional food commodities. Drastically improved recovery of STEC strains was shown for all 9 antibiotics examined in this study. The ability to accurately leverage AMR traits in specific pathogens for their recovery from high levels of background microbiota suggests this approach can be universally applicable in support of foodborne illness investigations.