A large fraction of foodborne illnesses are linked to (∼46%) leafy green vegetables contaminated by pathogens harbored in agricultural water. To prevent this, accurate point-of-production detection tools are required to identify and quantify bacterial contaminants in produce before consumers are impacted. In this study, a proof-of-concept model was engineered for a phage-based Escherichia coli detection system. We engineered the coliphage T7 to express alkaline phosphatase (ALP) to serve as the signal for E. coli detection. Wild type phoA (T7ALP) and a dominant-active allele, phoA D153G D330N (T7ALP*) was inserted into the T7 genome, with engineered constructs selected by CRISPR-mediated cleavage of unaltered chromosomes and confirmed by PCR. Engineered phages and E. coli target cells were co-incubated for 16 hours to produce lysates with liberated ALP correlated with input cell concentrations. A colorimetric assay used p-nitrophenyl phosphate (pNPP) to demonstrate significant ALP production by T7ALP and T7ALP* compared to the vector control (T7EV) (p≤ 0.05). Furthermore, T7ALP* produced 2.5-fold more signal than T7ALP (p≤ 0.05) at pH 10. Due to the increase in signal for the modified ALP* allele, we assessed T7ALP* sensitivity in a dose-responsive manner. We observed 3-fold higher signal for target cell populations as low as ∼2 × 10(5) CFU mL(-1) (p≤ 0.05 vs. no-phage control).