Over the last year, generative AI has exploded out of the dark corners of the tech industry to become a central object of public attention, imagination and investment. As generative AI tools are increasingly integrated into widely used products, ML engineers shoulder significant responsibility for the safety, risks and social impact of the systems they build. On the other hand, data engineers are expected to integrate a variety of new AI based tools into development workflows and data pipelines. In this talk, I will address the longstanding cultural gap between the two disciplines, and share thoughts on how data and machine learning engineers can work together to meet the challenges and opportunities created by the AI boom.