I left AI to do software. Here’s why.
If AI is a superpower, software is the vessel.
Four years ago, I hopped onto the AI bandwagon alongside many others. Today, I’m a software engineer.
Before I tell you why I made the switch, let me give you a quick TL;DR (I wrote a whole article on it here). I graduated college with a Bachelors in Economics in 2017 and joined an investment bank as a management associate. Doing mainly data analyst-related work, I quickly grew bored and decided to learn to code on the side. After acquiring some basic coding skills, I plunged head first into a Masters program with a specialization in AI back in 2018. With some purely academic/toy AI projects up my sleeves, I applied for an AI traineeship program that aims to train individuals up to enterprise level. Somehow, I passed their interview process.
Since then, I’ve been knee deep in the AI industry, working first as an AI engineer building AI Proof-of-Concept (PoC) for SMEs and then transitioned to a MLOps engineer handling model serving infrastructure and deployment pipelines on cloud.
Today, I’m a DevOps engineer, working mainly with low level Kubernetes components on a day-to-day basis.
