This as-told-to essay is based on a conversation with Jai Raj Choudhary, a 24-year-old AI engineer at StackAI, a no-code platform to build AI agents. His identity and employment have been verified by Business Insider. The following has been edited for length and clarity.
I went to grad school for a Master’s in AI from 2023 to 2025 and started my career in a data-focused role.
Around 2023 or 2024, LLMs were becoming more practical to use in real products, and AI stopped feeling like a whole research-driven field and more like an engineering problem.
I joined StackAI as an AI engineer in July. I got my job by reaching out to StackAI’s cofounder multiple times over LinkedIn. I started using the company’s platform as a student, so I messaged him and started posting about the company, giving advice about what worked and what needed to be added. They were growing fast and I went through six rounds of interviews and started working there.
This is part of an ongoing series about workers who transitioned into AI roles. Did you pivot to AI? We want to hear from you. Reach out to the reporter via email at [email protected] or secure-messaging platform Signal at aalt.19.
Now I build architectures for AI agents. One of the reasons I got offers from StackAI and other companies was because I understood data quality, the edge cases for the clients, and the matrix and the failure modes of the AI model or any LLM systems that we were using at the time.
StackAI didn’t ask about my degree during the interviews. In the interview, I said, “I know back-end, I know how to talk to data, and I understand the patterns that it follows.” They said that was the perfect background and they were able to help me grow from there to become an actual AI engineer. They asked if I knew how to operate computers in code and if I know Python. I gave them a couple of my projects and they gave me a take-home task to see how I built it.
After I started the job, they asked me where I went to school and what I studied. I love my professors, and I wouldn’t call grad school a waste because it gave me time to explore what I was interested in and helped me figure out what niche I wanted to work in. Occasionally, people do care about your background, but I’m not necessarily using what I learned in grad school on the job.
Moving to San Francisco
Moving to San Francisco made a huge difference in my career. This city is a different beast. When you come here, it’s a whole different culture because we don’t work 9-to-5, cushy jobs. We work 9-to-9, six days a week. You wake up, you think about the problem that a client had, and you sleep thinking about what isn’t fixed yet.
In San Francisco, even if you go out for a coffee, you’ll meet at least two founders who are working on something related to what you’re doing. I was able to network a lot.
At the end of the day, everyone is still researching AI. We’re still trying to find out what’s the best way to go about it. Having a conversation with someone who’s facing the same problem helps you work better.
Continuous learning
The best decision I made for my career was joining a startup for a job that I didn’t quite have the experience in and learning at StackAI.
But it’s not going to be like you go to sleep one day and wake up as an AI engineer the next. You need to study. Even if I spend 12 hours in the office, seven to eight of those hours I’m studying, and then three to four hours, I’m actually writing the code.
It gets overwhelming when you see 10 different AI courses coming out every day. What helped me is watching YouTube videos of the people who are actually building companies. Andrew Ng’s YouTube channel was also super helpful. I listen when I’m driving or in the gym. It doesn’t have to be a set time. It’s important that you keep turning your brain and taking in all these inputs.
You have to decide what’s important for you, but I was ready to sacrifice everything at the start of my career to grow as much as possible. It does take a toll on your personal time.
The culture of the company also helped because everyone that I work with is the best in what they do. If you ask them a question or if you collaborate with them on projects, it can really help you understand how they think. It really helps me to be surrounded with those people around the clock.
