AI in fintech is changing who gets hired. What companies really want, why junior roles are under pressure, and what it means for your career.

Most conversations about AI and jobs go one of two ways: either everything is about to collapse, or nothing will really change. Neither is useful if you're mid-career in fintech and trying to figure out what this actually means for you.
Here's what we're seeing from the inside.
At Evotym, we work with fintech companies across payments, crypto and web3 every day. We talk to hiring managers, take briefs, sit in on feedback calls. Over the past year, AI fluency has become a regular part of those conversations. Not as a technical requirement. Companies aren't looking for engineers who build AI systems. They want experienced professionals who've worked out how to use these tools to do their job better.
This spring, our team attended four industry events: UN:BLOCK, FIBE Berlin, HIPTHER Baltics: Riga and Baltic Fintech Days. The formats were different, the audiences were different, but one theme came up everywhere: AI. On stage and in hallway conversations between sessions, it was the same story – companies are actively figuring out how to work with these tools, what they expect from their teams, and what kind of people they want to hire next.
One of our Recruitment Partners Dari Lenko put it simply: "Most clients bring it up, even when it's not in the job description. The baseline they're looking for is someone who understands what AI is, how it can help their work, and where the limits are. Especially around data – knowing what you can’t share with these tools matters just as much as knowing how to use them."
According to Lightcast job posting data, employers now require AI skills in three times more job postings than two years ago, with a 109% jump between 2024 and 2025 alone. Companies tend to talk about what they want in conversations long before they put it in writing.
Look at the data and a clear pattern emerges: junior roles are under real pressure, senior ones less so.
A Harvard working paper published in May 2026, covering résumé and job-posting data across 65 million workers at more than 280,000 firms, found that at companies which adopted generative AI, junior employment fell by around 9% over six quarters compared to firms that hadn't. The reduction wasn't mainly from layoffs. Companies simply stopped replacing junior roles as they turned over.
An Oliver Wyman and NYSE survey of nearly 500 CFOs found similar expectations about the next three years:
Indeed Hiring Lab data from September 2025 adds to the picture: junior job postings dropped 7% year-on-year, while senior postings grew by 4%. Among 2025 graduates, job postings for new grads fell 15% year-on-year, while applications per role jumped 30%.
The tasks AI handles best (data entry, document review, routine analysis, basic reporting) are exactly the ones that are used to define the first two or three years of a fintech career. That's not a coincidence.
Entry-level roles shrinking is one thing. The deeper issue is what that means for the people who would have been your mid-level colleagues five years from now.
Think about how fintech expertise is actually built. No one walks into a compliance manager or senior sales role on day one. It comes from years of doing the structured, repetitive work first, reviewing documents, flagging transactions, processing applications, writing reports. That work isn't glamorous. But it's where you learn to spot a pattern that's slightly off, to judge which edge cases matter, to develop a feel for when the rulebook doesn't cover the situation.
That's what separates someone who's business-smart from someone who's book-smart. You can understand the framework perfectly and still not know when to apply it, and that only comes from doing the actual work.
When AI takes over those entry-level tasks, people entering the industry now skip that stage. They arrive well-educated and technically capable. But they haven't built the instincts that come from two or three years on the ground. The pool of genuinely experienced mid-level talent in fintech is going to be smaller ten years from now than it is today.
If you've spent several years building real expertise in fintech, the shift above works in your favour. Experienced professionals are becoming harder to find, which makes the ones already in the market more valuable.
But there's a condition. The combination companies are looking for right now is domain expertise plus practical AI fluency. Not certifications. Not knowing how every tool works under the hood. Just the ability to use AI to handle the parts of your work that don't need your full attention, and apply your thinking to the parts that do.
A few things worth doing now:
We covered the practical side of this, which tools are worth using and how to set up automations that actually save time, in our earlier piece: AI in Fintech: A Senior Professional's Guide to Using It Right.
AI in fintech isn't taking jobs away. What it's doing is raising the bar for which people get them.
Companies are moving fast with these tools internally, the talent pool of genuinely experienced professionals is going to get thinner over time, and the people who combine real domain expertise with practical AI fluency are the ones who stand out.
If you're already mid or senior level in fintech, those years of experience are more valuable now than they were two years ago. The question is whether you're making the most of them.
Ready to see what's open right now for your seniority level? Check current fintech roles on careers.evotym.com.