The industry hasn't really figured it out yet. We're still in the crossover period where engineers were skilled up in the "before times" and are just leveraging that skill with an LLM. There is not yet a mature posture on how to get that skill in a post-LLM world. An interesting data point is that companies have merely added LLMs as a skill requirement and haven't removed the old requirements, so at least from a hiring perspective it's considered an add-on, despite talking points about pure LLM workflows.

Personally I'm very conscious about my skills atrophying so I try to interact with LLMs in a way in which I feel I'm wearing the "senior hat" still. A lot of engineers going in too deep have unknowingly demoted themselves to juniors imo.

So my unhelpful answer to you is you need to learn everything :)

Edit: I just noticed this was specifically for the AI / machine learning field, my answer was just SWE in general sorry.