In this paper, a novel approach is proposed for genetically engineering bacteriophages. It is formed of two main modules: a predictor and a genome sequence generator. Convolutional Neural Networks are used to build the predictor while the generator is constructed based on Deep Generative Models. This paper concentrates in the architecture and the results for the predictor module. The evaluation results suggest that the proposed model has the potential to be further used to guide genetic edition of phages so as to improve phage therapy against bacterial infections.