There's more in common with other GPU architectures than there are differences, so a CUDA consultant should be able to pivot if/when the other players are a going concern. It's more about the mindset than the specifics.
ROCm is getting some adoption, especially as some of the world's largest public supercomputers have AMD GPUs.
Some of this is also being solved by working at a different abstraction layer; you can sometimes be ignorant to the hardware you're running on with PyTorch. It's still leaky, but it's something.
I used to use ROCFFT as an example, it was missing core functionality that cuFFT has had since like 2008. It looks like they've finally caught up now, but that's one library among many.
Programming languages are groups of syntax.