Working with AI. How to get it? These four people managed to change their careers

AI engineers, consultants, strategists and researchers are among the five fastest-growing jobs in the U.S., according to LinkedIn's “Jobs On the Rise 2026” report.

There is no single path to AI, and Business Insider spoke to four people who took very different paths. Here's how they changed their careers.

Natasha Crampton, director of responsible artificial intelligence at Microsoft

Natasha Crampton started as a lawyer and is now the principal director of responsible AI at Microsoft.

Her job involves working closely with engineering, sales and research teams to ensure they follow specific principles when building AI systems. It also includes external activities, such as helping to create new regulations and standards in this field.

Crampton studied information systems in addition to law and has always been interested in the intersection of technology, law and society. During the period when she dealt exclusively with law, she worked on technological issues, e.g. helping Microsoft in creating contracts.

He advises people looking to move into technology from other fields to start by using the technology in practice. He adds that many technical skills can be learned, so having a different education should not limit your ability to influence this area. In her opinion, “a huge part of the value” lies at the intersection of technical knowledge and social sciences.

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Georgian Tutuianu, AI engineer at HubSpot

Georgian Tutuianu has had several career changes in engineering – from structural engineering, to classical engineering, then programming, to AI at HubSpot.

He says his ability to get into technical details was a big asset during interviews and showed his experience in AI.

He also emphasizes that his CV includes a section devoted to his own projects. He only put one AI project there – and that was enough. The topic came up naturally during the conversation when he was asked about a situation in which he used or created an AI agent.

“It was such an interesting project that I could talk about it, and that was enough,” he says.

He adds that he also had to complete a programming task at home and discuss it later with the recruiting manager, but the interview did not include classic algorithmic tasks.

“Rather than the typical 'solve this algorithm in front of me' approach, it was more about 'can you build the things we care about? Show it to me,'” he explains.

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Jai Raj Choudhary, Engineer at StackAI

Jai Raj Choudhary moved from a data role to work as an AI engineer at the startup StackAI.

The 24-year-old landed the job by repeatedly contacting the company's co-founder on LinkedIn. He used the StackAI platform as a student, so he wrote to him and then started posting about and giving advice to the company.

He believes he got the offer because he understood data quality, customer edge cases, metrics, and failure modes of AI models and LLM systems.

He adds that moving to San Francisco — which has a 9-9-6 work culture — opened up new opportunities for him.

“It's not a comfortable 9-to-5 job,” he says. — We work from 9 a.m. to 9 p.m., six days a week. You wake up thinking about the customer's problem and go to sleep thinking about what hasn't been fixed yet, he adds.

Taking a job at a start-up that allowed him to grow and constantly learn was of great importance – Choudhary spent many hours every day learning.

Brit Morenus, senior manager of AI gamification programs at Microsoft

Brit Morenus, a 37-year-old senior AI gamification program manager, studied English, communications and marketing. She joined Microsoft about 13 years ago as a management assistant, and for the first 5.5 years she worked on a contract basis.

She later moved into a role related to gamification – using game mechanics to teach and promote Microsoft products.

She spent about a year earning certifications in game mechanics and was hired permanently in the role. Six years later, the opportunity arose to introduce gamification to the science of AI — and she spent three months learning about it.

He advises others not to let fear stop them from stepping outside their comfort zone. He also emphasizes that when working with AI, you need to understand how it works – not just use it. He adds that he does not regret studying English, because today it is more important than ever to understand how to use English in the context of AI.

“To a large extent, it's more about the English language than about artificial intelligence itself,” he argues.

The above text is a translation from American edition of Business Insider