Generative AI Engineering; An Overview
Hi there,
A quick one today 🤗
I've been working as a Gen AI Engineer for over six months now, and I've come to some realisations:
The first one is that AI Engineering isn't a well-defined field yet and the requirements or tasks vary based on the needs of the company/project at hand.
Secondly, An AI Engineer is a blend of a data scientist, machine learning engineer, and software engineer, particularly in backend development.
Why do I say so?
As an AI Engineer, you either use pre-built APIs or train your models, thus taking on the role of a machine learning engineer.
As an AI Engineer, you'll handle large datasets—cleaning, transforming, or otherwise manipulating them—tasks typically done by a data scientist or analyst.
You'll also develop APIs, manage backend tasks, and uphold software engineering principles, akin to a software engineer. This involves making API calls, integrating various APIs, processing data at the backend, and working with databases before exposing results to the frontend.
So, if you're building AI systems, be ready to wear multiple hats. You'll tackle various exciting challenges and make them work. Remember, you're a blend of an ML engineer, a data scientist, and a software engineer.
