As the annual campus recruitment season kicks off, hiring trends in the banking sector often serve as a key indicator of where the industry is headed. Major banks have now fully launched their 2026 fall recruitment drives, and a clear theme has emerged—AI and large-model expertise is the hottest commodity.

Unlike traditional tech companies, however, banks are no longer seeking pure coders. The most sought-after candidates this year are those who combine a deep understanding of financial services with hands-on AI capabilities. Many institutions have introduced specialized roles this year, including tech elite programs, intelligent R&D positions, and large-model application roles, signaling that the digital transformation of joint-stock and city commercial banks has now firmly reached the recruiting stage.

Beyond Coding: A Command of Large Models Is Now Essential

Job descriptions for technology roles at several joint-stock and city commercial banks have become more sophisticated and multidisciplinary this fall. For instance, China Merchants Bank has established an intelligent science R&D track within its head office functional positions, explicitly aiming to cultivate professionals "who understand both AI and business."

Shanghai Pudong Development Bank is prioritizing applicants with backgrounds in artificial intelligence, data science, and fintech, favoring those with cross-disciplinary academic experience. Ping An Bank is recruiting a cohort of digital-finance trainees, expecting them to integrate data analytics and intelligent technology with traditional banking operations to upgrade risk management, product design, customer service, and process workflows. The role requires proficiency in data analysis, computer technology, and AI tools.

China Guangfa Bank has opened its core AI positions to PhDs from top international universities, with hard requirements including mastery of large language models, multimodal technologies, and advanced algorithms like Mixture of Experts. On the city commercial bank front, Bank of Shanghai is focusing its head office fintech roles on the practical deployment of business systems, intelligent platforms, and digital tools.

Bank of Huzhou is advertising for a large-model application developer who must not only master deep learning, NLP algorithms, model fine-tuning, and reinforcement learning but also be skilled in prompt engineering, RAG retrieval augmentation, and intelligent agents. The role also demands familiarity with high-frequency banking AI use cases such as text parsing, knowledge-based Q&A, intelligent document generation, and automated scheduling.

The underlying message is clear: banks need professionals who can identify real pain points in financial services and answer critical questions. How can AI streamline credit approval? How can intelligent tools boost the efficiency of relationship managers? How can risk models be iterated for greater accuracy? The core competency banks truly value is the ability to translate technology into tangible business outcomes, which is why so many institutions are deliberately tilting toward candidates with composite backgrounds.

AI in Banking Moves to Scale

The collective rush to hire AI-integrated talent behind another key industry signal: banking has moved beyond the pilot phase and is now entering an era of large-scale AI deployment. Lou Feipeng, a researcher at Postal Savings Bank of China, notes that the rising demand for "tech plus finance" professionals reflects a transition in the banking industry's digital transformation into a phase of scaled AI application.

Interim reports from multiple listed joint-stock banks for 2026 reveal that AI has deeply penetrated the entire business chain—from customer acquisition and marketing to risk control, operations, and client services—and is now generating substantive value. China CITIC Bank reported that it has pushed AI development from "point-based exploration" to "systematic construction and scaled application," with cumulative AI service scenarios exceeding 1,900. Bank of Beijing has built more than 300 intelligent agents on its creation platform, evolving them from conversational tools into autonomous actors capable of executing tasks.

Bank of Jiangsu stated that its AI applications have replaced a cumulative 1.2 million working hours, enabling the replication of private-banking-level service capabilities. Meanwhile, Shanghai Pudong Development Bank noted that by the end of June 2026, its AI-related applications had shouldered more than 2,500 person-years of workload. AI has clearly become a new driver of productivity for smaller banks looking to compete.

Not a Passing Fad but a Structural Opportunity for AI Talent

From an industry perspective, hiring "AI plus finance" hybrid professionals is not a trend-chasing move but a structural shift in recruitment. As Lou Feipeng explains, AI's role in banking is evolving from a back-end forecasting engine to a front-end content producer. The competitive battleground among banks is shifting from branch scale and headcount to intelligent scenario-based service capabilities and compliant AI application levels. Understanding business operations and leveraging AI is becoming a standard requirement across all banking functions.

In the future, the industry is likely to embrace a new human-machine collaboration model: standardized, repetitive tasks will be handled by AI, while bank employees will focus on higher-value work that AI cannot replicate—such as maintaining premium client relationships, making complex risk decisions, delivering customized financial services, and driving innovation.

The modern banker will no longer be a pure finance professional or a pure technologist, but a versatile talent who understands finance, commands technology, and can deliver practical solutions. The talent market gap remains significant. Data from China's Ministry of Human Resources and Social Security shows that the domestic shortage of AI professionals has surpassed 5 million, with a supply-to-demand ratio of 1:10. For job seekers, seizing this opportunity to master both AI and business knowledge could well make them the biggest winners of this banking recruitment season.