Before artificial intelligence can take Wall Street jobs, start creating.
Posts for AI-related roles in banks are included JPMorgan Chase, Citigroup and Capital one an increase of 49% this year compared to 2025 to 139,819 listings, according to an analysis by the hiring company data company Draup made available exclusively to CNBC.
The fastest-growing area is the skills group that involves AI agents, according to Draup, who extract data from public job postings and platforms including LinkedIn. For example, references to agent orchestration, or the ability to design agents that work together on a task, increased by 1,721% this year.
“This is probably the hottest skill on Wall Street,” Draup CEO Vijay Swaminathan said in an interview. “This is a huge opportunity. They need people who understand data and people who understand AI and where to put it.”
The list of projects shows that Wall Street banks are moving beyond chatbots into the next phase of their AI strategy, which has implications for executives, employees and shareholders. To deliver on AI’s promise to boost productivity and automate repetitive tasks, banks are moving toward a future filled with armies of agents handling the bulk of their workforce.
While the previous wave of AI hiring was dominated by engineers and data scientists who built models or adapted them to company data, the boom has expanded to include people responsible for putting AI directly into business lines.
The deployment of AI in financial institutions often requires several specialized agents: one to review raw data, another to analyze documents and a third to check regulatory compliance, for example.
The workers involved in this process, often called advanced development engineers, require a combination of technical abilities and domain knowledge of a specific business or function, from the trading desk to back-office operations and human resources, according to Swaminathan.
“There is a lot of complexity in the company,” says Swaminathan. “Sometimes the complexity is visible, but often it is hidden. It takes a long time to even automate a simple process.”
For example, creating a team of agents to automate the approval of employee vacation requests creates a web of edge cases and special exceptions, he said.
Agent orchestration skills are particularly relevant to forward-deployed engineers, as their job is to determine which agents are needed, what they do and which technologies to use, CEO Draup said. It also includes deciding when human supervisors should be involved, he said.
Agent technology stack
Other in-demand skills associated with building AI include understanding tools and techniques that give agents the ability to solve problems.
References to LangGraph, a framework for building multistep workflows, jumped 679%, while mentions of LlamaIndex, which helps connect AI applications to data, rose 291%, according to Draup’s analysis. References to retrieval-augmented generation, or RAG, a technique to provide information to AI models from corporate databases, increased by 259%.
However, beyond technical abilities, there is a greater emphasis on so-called soft skills.
“Our analysis shows that there is a new focus on soft skills like problem solving, creativity, the ability to ask difficult questions, being assertive. [when it comes to] a deeper understanding of the process,” he said.
Other areas of growth in AI include those responsible for building fences around evolving systems, including the demand for risk and control infrastructure.
References in job postings related to “responsible AI” increased by 657% this year, according to Draup, while those mentioning AI governance and risk management increased by 394% and 359%, respectively. The security team also focuses on preventing third-party devices or external model connections from creating systemic vulnerabilities.
Skills related to government currently have more than 16,000 references in Draup’s data, almost double the approximately 8,400 related to training, deploying and running models.
“There is a lot of focus on making sure that the third parties that are used in these products are not going rogue from a cybersecurity standpoint,” he said.
Roles related to generative AI and agents typically pay more than tech roles elsewhere in finance, with generative AI managers paying an average base salary of $190,000, according to Draup.
Despite the higher salaries, filling these specialized roles remains a challenge, Swaminathan said.
To bridge the gap, major banks lean heavily towards internal reskilling programs to train existing developers and domain experts, he said.
Building-out itself will create a ripple effect: JPMorgan CEO Jamie Dimon has talked about “big redeployment plans” as AI takes over more work.
“I prefer soft skills with proper technical skills, people will adapt and learn,” says Swaminathan. “It’s an exciting time for the right talent.”
