The First Wave Of AI On Wall Street Is About Hiring, Not Replacing

Before artificial intelligence begins displacing large numbers of Wall Street workers, it is creating a new class of jobs across the banking industry.

Posts for AI-related roles at major banks, including JPMorgan Chase, Citigroup and Capital One, climbed 49% this year to 139,819 listings, according to an analysis from enterprise hiring data firm Draup, provided exclusively to CNBC. The surge underscores a shift in how financial institutions are approaching AI: not merely as a back-office efficiency tool, but as a strategic capability being embedded across core business lines.

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Agent Skills Are Emerging As The New Hiring Frontier

The fastest-growing area is centered on AI agents, according to Draup, which aggregates data from public job postings and platforms such as LinkedIn. References to agent orchestration — the ability to design multiple agents that work together on a task — jumped 1,721% this year.

“This is arguably the hottest skill on Wall Street,” said Vijay Swaminathan, CEO of Draup, in an interview. “It’s a massive opportunity. They need people who understand data and people who understand AI and where to put it.”

The hiring data suggests banks are moving beyond chatbots and pilot projects into the next phase of AI deployment, one that could reshape productivity, operations and even headcount planning. To deliver on AI’s promise of automation, firms are increasingly building systems in which agents handle discrete parts of a workflow, from data inspection to document review to compliance checks.

From Engineers To Embedded Business Builders

Earlier AI hiring waves were dominated by engineers and data scientists building models or adapting them to proprietary data. The current phase is broader. Banks are now hiring people who can embed AI directly into business functions.

That often requires what the industry calls forward-deployed engineers — professionals who combine technical fluency with deep domain knowledge, whether in trading, operations or human resources.

“There is a lot of complexity in an enterprise,” Swaminathan said. “Sometimes these complexities are visible, but many times they are hidden. It takes a long time even to automate a simple process.”

He pointed to something as routine as automating employee vacation approvals. What appears simple on the surface can quickly become a network of exceptions, edge cases and policy-specific rules.

For that reason, agent orchestration has become especially valuable. The role requires deciding which agents are needed, what each should do, which tools to use and when human oversight must remain in the loop.

The Tech Stack Behind The Buildout

The skills in demand also point to the technical architecture supporting the AI push. Mentions of LangGraph, a framework for building multistep workflows, rose 679%, while references to LlamaIndex, which connects AI applications to data, increased 291%. Mentions of retrieval-augmented generation, or RAG, climbed 259%, according to Draup.

At the same time, banks are placing more emphasis on the human skills needed to deploy AI effectively.

“Our analysis shows that there is a renewed focus on soft skills like problem solving, creativity, ability to ask tough questions, being assertive [when it comes to] deeper understanding of the processes,” Swaminathan said.

Governance And Risk Are Becoming Core Priorities

As AI becomes more deeply embedded in financial institutions, governance has emerged as a major hiring theme. Demand for “responsible AI” roles surged 657% this year, while references to AI governance and risk management rose 394% and 359%, respectively, according to Draup.

Security teams are also focused on limiting systemic vulnerabilities, particularly those created by third-party tools or external model connections.

Governance-related skills now account for more than 16,000 references in the Draup data, nearly twice the roughly 8,400 tied to training, deploying and running models.

“There is a lot of focus on making sure that the third parties that we are using in these products are not going rogue from a cybersecurity standpoint,” Swaminathan said.

Higher Pay, Scarce Talent, And Internal Retraining

The rise in demand is also showing up in compensation. Roles tied to generative AI and agents typically pay more than other technology positions in finance, with generative AI managers earning a median base salary of about $190,000, according to Draup.

But higher pay has not solved the talent shortage. These are highly specialized roles, and banks continue to struggle to fill them.

As a result, major institutions are leaning heavily on internal reskilling programs to train existing developers and business experts, Swaminathan said.

The shift is likely to have broad workforce implications. JPMorgan Chase CEO Jamie Dimon has spoken of “huge redeployment plans” as AI assumes more work, reflecting a broader trend across finance: jobs are not simply disappearing, but being reconfigured.

“I think the more we prioritize those soft skills with the right amount of technical skills, people will adapt and learn,” Swaminathan said. “It’s a very exciting time for the right talent.”