Although your current role wouldn’t seem very senior at a large organizational, “senior“ is a relative term and at this company it seems like you are the engineer with ownership responsibilities over the end-to-end software development of a production system. So it might still be reasonable to use a senior title if there are other benefits
It’s probably not going to work as a defense against training LLMs (unless everyone does it?) but it also doesn’t have to — it’s an interesting thought experiment which can aid in understanding of this technology from an outside perspective.
I agree with how you characterized it and the term “ai engineer” didn’t resonate with me as defined by the author. If such an engineer doesn’t need to know about the data involved (“nor do they know the difference between a Data Lake or Data Warehouse”) then I don’t think they will be able to ship an AI/ML product based on data.
New titles can be helpful for sorting out different roles with some shared skillsets such as the distinction which emerged between Data Scientist and ML Engineer at some companies to focus the latter on shipping production software using ML.
Time zones are an endless source of frustration, this one doesn’t sound too bad though:
https://github.com/LemmyNet/lemmy/pull/3496