AI is expected to fuel Wall Street's tech hiring in 2025. Headhunters break down what you need to know to get a leg up.

A few years ago, Matt Stabile, a tech recruiter who works with buy-side firms including Two Sigma and Susquehanna International Group, could almost guarantee an interview with a hiring manager if a candidate was coming out of a FAANG company.

"Now, due to overhiring and layoffs, those resumes seem to be a dime a dozen," Stabile told BI.

It's true that Big Tech companies have shed thousands of workers this year, flooding the job market with resumes touting the same companies, like Meta and Amazon. And only certain divisions of Big Tech companies on a resume will catch hiring managers' eyes, like Google's DeepMind, for instance, Stabile said.

Finance firms witnessing the AI transformation from the sidelines want to get in on the action and build their own homegrown solutions. That's created demand among hedge-fund clients to ask for technologists specifically from Nvidia, Hodzic told BI.

"There's definitely an inherent need for people to understand the infrastructure side as well, how to actually construct the computer in the right way to be able to process some of this information and what quality of chips are needed in order to actually produce the output they're looking for," Hodzic said.

Stabile is seeing the same, with hiring managers getting excited to see talent coming from the $3.6 trillion chipmaker, AI startup Anthropic, and ChatGPT-maker OpenAI. He said these are the resumes that are getting through and being considered over all the others.

Even if you haven't worked at any of these companies, Stabile said experience and exposure to their software tools is still a highly sought after skill. He specifically highlighted the Nvidia Triton Inference Server, an open-source software that's key to deploying and executing AI workloads, Nvidia TensorRT-LLM, used to optimize the performance of large language models, and Nvidia Fleet Command, which is important for scaling AI deployments.

If you haven't worked at a large AI company, or haven't worked with their latest products, not all hope is lost.

Wall Street banks especially rely heavily on legacy technologies. Some are built on codebases that have likely been around longer than the developer working on it has been alive. To be clear, that hasn't stopped financial firms from building entire businesses and offerings on modern technology.

What that has introduced, however, is the need to ensure that systems old and new can work together and exist in the same environment without introducing bugs or dependency issues. And in the case of firms moving on-premise systems to the public cloud, sometimes entire back-end systems have to be rebuilt.

As a result, hiring managers often light up when candidates can talk about their experience with software migrations, Selby Jennings' Hodzic said. If you've shifted data or software from one system to another, or translated code from one language to another, be sure to bring it up during the interview process.

"People who can demonstrate that engineering skillset of recreating and reconstructing things are really sought after," Hodzic said. "I think what a lot of clients want are people who can come in and show them what's not working well, how to iterate and how to improve, and then actually do it."