What is AI Engineering?

AI engineering is an emergent discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts. Where it is implied the subsets of AI are also included in the field of AI [Software] Engineering i.e. machine learning, deep learning, reinforcement learning, and quantum learning. Unpacking that a little more; AI focused projects should use software engineering principles and best practices. Individuals (like myself) whose start in the field of AI began in Data Science and other quantitative disciplines, should consider re-tooling their skills to become less dependent on Jupyter notebooks and instead be concerned with modular design of (code) packages, object oriented programming, formatting and styling, and being okay with (if a Python programmer) tools like Python's standard GUI toolkit -- tkinter, and matplotlib; and tasks like git versioning using tools such as GitHub or GitLab and to an extent, an understanding of the administrative backend of these tools. Maybe an even more concise definition is simply: less data science and quantitative business analytics practices, and more software engineering practices.