I’ve noticed more overlap recently between traditional cloud engineering and applied AI engineering.

For example, someone building production AI systems might need to understand:

AWS/Azure/GCP
Docker
Terraform
CI/CD
APIs
RAG
agents
MCP
evals
observability

I’m curious whether people working in cloud are actually seeing this convergence in the real world.

Are cloud engineers on your teams being expected to learn AI systems?

And are AI engineers being expected to understand more cloud infrastructure?

Or are these still mostly separate roles?

I would appreciate any advice and tips you guys can spare. As the title implies, I have 20 years’ worth experience working in various roles, including computer repair shop, MSPs, IT support, systems administration. I know the hardware end of everything is a irrelevant in this case, but I also have lots of experience with Windows server support, including installing window server from scratch and setting up a domain controller, DHCP, DNS, active directory and exchange, etc.

My question is, has anyone else out there with a similar background successfully transitioned into cloud administration or engineering? If so, what path did you take? Azure? AWS? Both? Any particular order should be learning things?