>Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves?

I'm definitely not any authority on the matter -- also self taught, but I don't think so.

Having a conceptual understanding of the math is probably a really good idea, but I imagine there's quite a bit that can be hidden behind an api that you can essentially say "does xyz by means of magic".

I imagine this winds up creating three distinct roles: - Focusing on improving the model's usefulness - Focusing on implementing the model for optimal performance - Focusing on using the model within a larger application

I say "creating", but I imagine this is also probably roughly the current status quo.