Banks launch strong AI talent drive

Several Chinese lenders have recently launched special recruitment programs targeting high-level artificial intelligence talent, accelerating their push into the financial AI arena. The trend underscores the banking sector's growing urgency to advance its digital and intelligent transformation.

The latest hiring drive focuses on core areas such as large language model development, AI application deployment and technology architecture planning. Entry requirements have been significantly raised, with most positions requiring candidates to hold PhD degrees from internationally renowned universities, possess work experience at major overseas institutions, and demonstrate expertise in LLM development, deep learning frameworks and other advanced AI technologies.

Yang Haiping, a researcher at the Shanghai-based SIFL Institute, said that the large-scale recruitment of top-tier AI talent is an important step for banks seeking to gain an early-mover advantage in AI applications and upgrade their digital finance strategies. The move will accelerate intelligent innovation in banking operations and management, reshape the industry's technological foundation and core competitiveness, and fundamentally change approaches to talent development in the sector.

Bank of Communications is recruiting senior AI experts for its financial technology department and fintech innovation research institute. Applicants are required to hold a PhD from a globally recognized university and have at least three years of relevant experience at a major overseas financial institution or international organization. Candidates with backgrounds in AI, data mining or computer vision, strong expertise in machine learning, deep learning and graph algorithms, as well as experience in AI strategy planning or generative AI model development at large institutions, will receive priority consideration.

Bank of China is hiring for an AI planning and research position in the fintech department at its head office. The role will be primarily responsible for developing the lender's AI framework and promoting the integration of AI technologies into core business operations. Preference will be given to candidates with experience in AI research and development at leading global tech companies, major financial institutions' AI centers or top-tier AI laboratories. The position also emphasizes the integration of technology and finance, requiring at least five years of fintech experience and familiarity with banking operations as well as risk and compliance requirements.

China Guangfa Bank has also recently opened an AI-related position at its head office, focusing on forward-looking research and commercialization of LLMs. Candidates are expected to be proficient in cutting-edge technologies such as LLMs and multimodal systems. The position is open only to PhD holders from prestigious overseas universities with at least three years of experience at internationally recognized companies or overseas financial institutions.

Gao Zhengyang, a special researcher at Jiangsu Su Merchants Bank, said lenders are competing intensely for top AI talent because the technology is rapidly penetrating every aspect of banking, including risk management, marketing, operations and customer service. Professionals with cutting-edge technical expertise can help banks build proprietary and controllable AI systems to support the intelligent upgrading of their businesses.

Gao said this year's AI recruitment drive reflects the banking sector's strategic ambition to use AI to fundamentally reshape banking operations. As competition shifts from traditional business capabilities to data management and intelligent decisionmaking, banks increasingly need multidisciplinary professionals who possess both advanced algorithmic expertise and a deep understanding of financial services.

A report released by PwC in March found that among surveyed financial institutions in the banking, insurance and asset management sectors in the Chinese mainland and Hong Kong, more than 75 percent plan to position AI as a "strategic transformation engine" to revolutionize and expand existing services, or as a "new revenue pillar" to generate new income streams through innovative services, over the next three to five years.

Looking ahead, Tian Lihui, a professor of finance at Nankai University, said the demand for AI talent in the banking sector will follow three major trends: talent shortages will increasingly be concentrated among hybrid professionals who combine business expertise with algorithmic skills; AI-related positions will gradually expand from the head office to branch networks and subsidiaries; and AI governance and compliance positions will become a critical requirement across the industry.

In the long run, Tian said, banks need to establish sustainable talent development systems, optimize performance evaluation mechanisms, and allow sufficient time for technology refinement.

AI has already permeated virtually every aspect of banking operations in China.

Industrial and Commercial Bank of China has deployed more than 500 AI application scenarios across over 30 business areas, while China Construction Bank's AI applications cover nearly 400 scenarios, leveraging AI to empower the entire credit approval process. Bank of Communications has deepened its AI applications in areas such as cross-border trade, wealth management and the digital transformation of retail banking operations, with its intelligent computing capacity increasing by more than 50 percent year-on-year in 2025.

Demand for tech professionals is growing rapidly. The combined number of tech personnel employed by China's six largest State-owned commercial banks rose from more than 111,100 at the end of 2024 to over 135,800 by end-2025, representing a year-on-year growth of 22 percent, significantly outpacing changes in overall bank staffing levels.

Dong Ximiao, chief economist at Merchants Union Consumer Finance and deputy director of the Shanghai Institution for Finance and Development, said China still faces a significant shortage of fintech talent, and there remains a clear mismatch between university training programs and industry needs.

Dong said large financial institutions should take the lead in tech development and application, while sharing excess capabilities and talent resources. Smaller institutions should cooperate with leading financial institutions and tech firms to accelerate the integration of technology and business operations.

He suggested that financial institutions foster an open and inclusive culture that tolerates experimentation and failure, and build a comprehensive talent ecosystem through recruitment and promotion mechanisms.

Dong said banks should ensure that chief information officers are empowered with clear responsibilities, authority and resources. At the same time, AI-related risks should be fully incorporated into enterprise-wide risk management frameworks, with comprehensive measures adopted to prevent and address risks.