I'd confidently call myself an AI engineer[1] though technically my title is Data Scientist.

My day generally looks like this:

8am read email

9am standup

Usually some kind of meeting (planning, 1-on-1s, retro, something else)

Heads down time

Lunch, read at the park

Heads down time until 5pm

Fridays we alternate having a team symposium or a book club that I lead. Right now we happen to be reading the book referenced in [1].

Tasks are usually code based. Fixing/extending the agent code, tool writing/bug fixing, writing pipelines for data ingestion, etc.

Part of my job is technology recommendations, so staying on top of the fast moving field and being able to match problems to best-in-class/stable tech choices is a must. I have a long software engineering background and am an excellent debugger - I rarely get stuck on a bug, only slowed down. I can rapidly prototype an idea, and then take it all the way to development, qa, and deployment, given the right resources.

1. In line with Chip Huyen's AI Engineering book. ISBN 978-1098166304