Wall Street AI hiring is shifting from "model building" to "deployment and implementation," with new types of engineers becoming the most sought-after talent.

Wall Street AI hiring is shifting from "model building" to "deployment and implementation," with new types of engineers becoming the most sought-after talent.

Artificial intelligence is sparking a new talent war on Wall Street, and the focus of this war has shifted from model builders to hybrid engineers who can directly embed AI into business.

On October 4, according to an analysis exclusively provided to CNBC by corporate recruitment data company Draup, the number of AI-related job postings from banks such as JPMorgan Chase, Citigroup, and Capital One surged by 49% year-on-year to 139,819 this year.

Among them, the number of job citations related to "Agent orchestration" has surged by 1,721% this year, making it one of the most sought-after professions in the financial industry right now.

This trend indicates that Wall Street is accelerating its transition from the chatbot stage to the next stage where multiple AI agents collaborate to handle a large volume of business, which will have a profound impact on banks' employee structure, management strategies, and shareholder return expectations.

Compensation for generative AI-related positions is also significantly higher than for other technical roles in the financial industry, with the median base salary for a generative AI manager being approximately $190,000.

"Agent orchestration" has become the hottest skill, with demand exploding.

Draup analyzed publicly available job postings from platforms like LinkedIn. Data shows that job postings related to "Agent Orchestration Engineer" have seen a 1,721% jump in citations this year.

Agent orchestration refers to the ability to design multiple AI agents to work together to complete a task. For example, one agent might review raw data, another might analyze documents, and a third might verify compliance, with all three working in concert.

Draup CEO Vijay Swaminathan stated in an interview:

This is arguably the most sought-after skill on Wall Street right now, representing a huge opportunity. Banks need people who understand data, AI, and how to implement them effectively.

Behind this demand lies the urgent intention of banking institutions to truly implement AI across their business lines. To deliver on AI's promise of improving productivity and automating repetitive tasks, major banks are accelerating the development of a future where AI agents handle more of the workforce.

Emerging Roles: Frontier Deployment Engineers Become Key Positions

This wave of recruitment has clearly moved beyond the earlier focus on engineers and data scientists primarily engaged in model building, extending to "forward-deployed engineers." The core responsibility of these talents is to directly embed AI into specific business scenarios such as trading desks, compliance departments, and back-office operations.

Vijay Swaminathan pointed out that these types of positions require both technical skills and expertise in specific business areas, covering everything from trading desks to back-office operations and even human resources, and the complexity of the tasks far exceeds expectations.

Vijay Swaminathan emphasized:

There is a great deal of complexity within enterprises, some of which is obvious, but much of it is implicit. Even automating a simple process can take a significant amount of time.

He used the automatic approval of employee leave applications as an example to illustrate that this scenario alone can generate a large number of edge cases and special exceptions.

Agent orchestration skills are highly relevant to the work of front-end deployment engineers, as the latter need to determine which agents are necessary, what functions they should perform, what technologies they should use, and when human intervention and supervision are required.

The demand for underlying technical tools related to building intelligent agents has also increased significantly. According to Draup data:

LangGraph, used to build multi-step workflow frameworks, saw its reference count jump by 679%.LlamaIndex, which helps AI applications connect to data sources, saw a 291% increase in citations.Cited data for Retrieval Augmentation (RAG) techniques, used to input enterprise database information into AI models, surged by 259%.

At the same time, the importance of soft skills is also rising. Vijay Swaminathan said that Draup's analysis shows that the industry is re-emphasizing soft skills such as problem-solving, creativity, the ability to ask deep questions, and a deep understanding of processes.

As AI systems are deployed more extensively in financial institutions, the demand for positions related to risk management and compliance governance is also surging, with a growth rate no less than that of technical development positions.

According to Draup data, citations of "responsible AI" in job postings surged by 657% this year, while citations related to AI governance and risk management jumped by 394% and 359%, respectively.

The total number of job citations for governance skills has now exceeded 16,000, almost double the approximately 8,400 citations related to model training, deployment, and operation.

Vijay Swaminathan stated that one of the security team's current priorities is preventing systemic security vulnerabilities from being created by third-party tools or external models. Vijay Swaminathan said:

Ensuring that the third-party tools we use in these products do not 'get out of control' at the cybersecurity level is a key concern at present.

High salaries coupled with a persistent talent shortage have prompted banks to bet on internal retraining.

Despite attractive compensation—the median base salary for generative AI managers is around $190,000, higher than other tech roles in the financial industry—filling these specialized positions remains a challenge.

Vijay Swaminathan stated that to bridge the talent gap, major banks are vigorously promoting internal retraining programs to systematically upgrade the skills of existing developers and business experts.

This wave of AI development will also have a ripple effect. JPMorgan Chase CEO Jamie Dimon has repeatedly mentioned a "massive redeployment plan" following the takeover of more jobs by AI.

Vijay Swaminathan holds a relatively optimistic view on this:

I believe that as long as we prioritize developing soft skills on top of the right technical capabilities, people will be able to adapt and learn. This is a very exciting time for the right people.

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