As modern life science research shifts from an observational field of science to a field of engineering biology, computational techniques are more relevant to every aspect of the field. Artificial intelligence (AI) is emerging as a massive accelerator of biological engineering for its ability to learn the design paradigms of life (DPoL) and understand the genotype-to-phenotype (G2P) relationships of organisms. The reception has been mixed, however, as opportunities across health, energy, environment, agriculture, and industrial materials are confronted with emerging biosecurity risks across novel pathogens of concern and operational knowledge of biological engineering. There is an urgent need for research to be conducted at the intersection of AI security and biosecurity and the establishment of a violet teaming paradigm where research focused on risk is paired with those focused on the opportunity to minimize the downside and maximize the upside provided by AI in the life sciences.