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World of Software > News > I’m a 26-year-old Google engineer who transitioned to an AI job for a year. Here’s how I did it.
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I’m a 26-year-old Google engineer who transitioned to an AI job for a year. Here’s how I did it.

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Last updated: 2025/12/04 at 5:18 AM
News Room Published 4 December 2025
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I’m a 26-year-old Google engineer who transitioned to an AI job for a year. Here’s how I did it.
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  • A 26-year-old Google software engineer says it took her a year to transition to an AI team.

  • Maitri Mangal spent two hours a day on further training and continues to spend hours learning every week.

  • She says creating content has helped her understand the material and suggests solo projects to capture concepts.

This as told-to essay is based on a conversation with Maitri Mangala 26-year-old software engineer at Google, based in New York. Her identity and employment have been verified by Business Insider. The following has been edited for length and clarity.

When I started as a software engineer, my father, who also works in tech, kept telling me to get into AI.

I turned it down because I was just starting my tech career, and no one was really talking about AI in 2019 unless they had a PhD.

In 2023, the technology industry changed and everyone started getting involved with AI. That led me to pursue AI as a job and also create content about it. When trying to become part of an AI team, I think a strong presence and personal brand are crucial for others to take you seriously.

In my three years at Google, I’ve changed roles three times, most recently moving to the Workspace AI team.

It is important to distinguish between an AI machine learning engineer and an AI software engineer. An AI ML engineer creates the model, trains it and evaluates it. An AI software engineer integrates AI capabilities into software applications and builds APIs and infrastructure to serve the model to the end user.

My move to an AI team didn’t happen overnight. I had to spend about a year of further training through courses and creating content on the material, which required me to learn the concepts.

This is how I made the switch:

Create content about AI

In the spring of 2024, outside of work, I started creating tech content on Instagram and LinkedIn. That became an important factor in my transition to an AI team.

Creating content motivated me to keep learning and also gave me the confidence to share what I knew. Once I started seeing how much it helped people, I wanted to learn more. So that’s where the upskilling started and I started taking courses to understand the basics of AI.

Eventually, I started applying to AI teams at Google. I felt that if I was going to spend so much time upskilling and creating content about AI, I had to make the most of what I had. I started looking for new positions in January, about seven months after I started training. I got the new job in March.

I still spend an hour a day on further training

I usually take Google’s internal courses to improve my skills. Coursera also has great courses.

The easiest way to get started is to follow the basics of AI, such as Google’s Introduction to Genative AI and Google Prompting Essentials. Because I have a computer science background, I was able to delve further into concepts such as linear regression and vector analysis.

I took courses about two hours a day, but to absorb the material I had to talk about it, not just read it. When I articulated the concepts by creating content, it helped me understand the material.

I also get feedback from my followers, and when they ask follow-up questions in the comments, I can go even deeper into understanding a topic. Talking to friends or teammates who are enthusiastic about AI also helps me understand the material better.

It is very difficult not to learn in this area. I’m not necessarily still spending two hours a day on courses, but I’m still spending about an hour a day upskilling, whether that’s in the form of in-house training for my job, or watching YouTube courses for the content I create.

Not everyone wants to create content, so moving to an AI team isn’t always the best way to go. If you’re just starting out in tech, my biggest piece of advice would be to take on projects. You should definitely take courses on AI, but staying up to date with the news and doing AI projects also helps a lot. Many AI courses have users doing mini projects so you can learn how to work with them.

Because I applied internally, I didn’t have to go through the same application process. However, I still had to submit my resume, which listed all my side projects, and I think that really helps.

Read the original article on Business Insider

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