The Absurdity of the term "AI Engineer"

Catching up with a friend recently, he mentioned that his org was looking to hire an "AI Engineer".

The platform is a stock-standard B2B CRUD SaaS, so this statement confused me.

I could not imagine why they would be doing sophisticated, low-level AI work.

When I pressed for details, it became apparent that they did not, in fact, want an "AI Engineer".

They wanted an engineer to build a chatbox that called ChatGPT with company documents as prompt context.

I don't know about you, but "back in my day", integrating third-party SDK's/API's for app functionality was most of the product work required to launch a SaaS.

Slap a UI on top of CRUD forms, and a slew of libs for things like: Auth, Email/SMS, Storage, Billing, Cloud Infra, etc...

Any engineer who has spent time in the "launch SaaS fast" startup gauntlet will tell you that integration is at LEAST half of greenfield app work.

Let's play a game called "Guess The Job Description".

A "Database Engineer" is someone who:
- Installs and uses database client libraries
- Develops features of a database engine
A "UI Engineer" is someone who:
- Integrates UI libraries like Material UI, Ant Design, or shadcn
- Designs and develops user interfaces for an application

Aren't these fun! Okay, one more:

An "AI Engineer" is someone who:
- Installs, uses, and configures LLM libraries with appropriate context
- Works on ML model design, training, and implementation

In closing, the next time I hear someone describe themselves as an "AI Engineer" for consuming a third-party SDK, I'm going to have an aneurysm, I think.

AI Use Disclaimer: claude code was used to generate the OpenGraph SVG image

No part of the prose was machine-generated. You will not find machine-written prose on this blog. I consider it deeply disrespectful.