If you’re looking for answers on how generative AI is changing Wall Street, look no further than its technologists.
Software engineering divisions have been at the forefront of Wall Street’s generative AI evolution. They’re not just designing and building the systems. Developers have been some of the earliest adopters of AI, using it to do tasks from writing and testing code, to documenting what it does, and reconfiguring decades-old platforms written in outdated coding languages.
The proliferation of AI in the finance industry’s tech ranks has some questioning the role of humans in the process as engineers delegate much of their coding work to machines. And it’s no wonder. Tech execs at leading institutions are discovering that generative AI is starting to code better and faster than them.
Amid this seismic change, Business Insider spoke with four industry technologists and a recruiter for advice on what software engineers should do to find success in Wall Street’s AI era. The words of wisdom come from top tech execs at financial powerhouses like Goldman Sachs, Morgan Stanley, and Point72. They described how the role of developers has evolved and how technologists can keep their edge.
Ilya Gasysinky, Point72 CTO
As the top tech executive at Steve Cohen’s hedge fund Point72, Ilya Gasysinkiy is guiding the firm’s technologists through an unprecedented period of change. Gaysinskiy recently told BI how he’s trying to reimagine the developer experience as the fund invests more in AI talent and tools.
Wall Street is ripe for AI disruption, and his advice to developers is to embrace the disruption. Code generation is one area where he sees big potential — in the past few weeks he joked how how AI is starting to get better at coding than him.
“If you want to succeed as an engineer, you just have to embrace the fact that the environment is constantly changing,” Gaysinksiy said.
Hina Shamsi, Morgan Stanley managing director
As AI increasingly automates some of the technical aspects of developers’ jobs, it’s important to “think more broadly about your role, not just as a technologist, but as a business technologist,” Hina Shamsi told BI. Shamsi is the CTO for Morgan Stanley’s wealth management and institutional businesses and also sits on the technology operating committee that drives tech and strategy across the firm.
Engineers should zoom out and make sure they understand the business to see how the technology components are going to come together, she said. Her advice is to focus “on the end-to-end business and see how you can leverage the tech to create more value for the business.”
Melissa Goldman, Goldman Sachs partner
Be prepared to spend more time designing and managing, according to Melissa Goldman, the global head of engineering for global banking and markets at Goldman Sachs.
Now that engineers can delegate much of the toil of their day-to-day jobs, like sifting through code for bugs or typos and building standardized tooling, they’ll be able to show off their chops through design aspects.
Also, think about how to best prompt AI to achieve the desired outcome, a practice called prompt engineering. It may require new management skills, similar to how software managers have learned how to get the best out of their direct reports.
“Maybe all the skills we’ve been teaching people how to manage other developers, we now teach them how to manage the various services and capabilities” like generative AI, Goldman said.
Brent Foster, TD vice president of software
Generative AI is changing what Brent Foster looks for in new hires. Foster is a vice president of software at TD who is focused on tech recruitment and development.
The former Amazon and Capital One executive said there’s a bigger emphasis on technologists’ soft skills, such as communication and collaboration. Also important is being able to showcase an ability to adopt new generative AI tools, such as GitHub Copilot, which he said the bank has rolled out to its tech population.
“The folks who are going to be the most successful are the ones who can most effectively take advantage and fully leverage those capabilities in the best way,” he said of generative AI tools.
“Learning agility is a soft skill that’s become very important today,” Foster said.
Ben Hodzic, Selby Jennings managing director
Getting experience using generative AI as an engineer is great, but what’s even better is rolling up your sleeves and building or implementing AI at your company. Doing so may help you climb the career ladder, according to Ben Hodzic, a recruiter at the Wall Street-focused search firm Selby Jennings.
Hodzic works with hedge funds and investment banks and said prospective employers want candidates to drill down on how they helped develop the roadmap and architecture of AI software. Ultimately, they’re interested in how well the candidate knows the nuts and bolts of building AI systems and how easily the technologist could replicate it at their company.
“Candidates get tripped up by only talking about how they use AI, how it adds value, and the use cases. But the replicability and architecture aspect is super important,” Hodzic said.
Read the full article here
