A job posting has caused a stir in the private equity circle! You can apply if you're 18 or older with a high school diploma, but you must "understand AI."

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The investment research positions in the private equity industry have long been the “main battlefield” for graduates from prestigious universities. However, recently, a recruitment announcement from a private equity firm in Beijing has completely shattered the industry’s implicit barriers of education and age—anyone aged 18 or older, with at least a high school diploma or equivalent, can apply.

Once the information was released, it sparked heated discussions in the private equity circle: do core investment research positions really no longer value educational background or require investment experience? The answer is not absolute. It is understood that the core requirement for this recruitment is that candidates must provide detailed insights on AI usage, usage records, and representative cases. Among them, the Chief Artificial Intelligence Officer position clearly states that candidates must promote the company’s deep integration with AI, comprehensively reshape business operations, and achieve goals such as multiple productivity improvements and reduced operational costs.

In the AI era, capability outweighs academic credentials; will artificial intelligence really “disrupt” the private equity industry? Opinions in the industry vary.

The private equity institution that broke industry norms is “Zhiyu Zhi Shan”. Its official WeChat recruitment advertisement indicates that individuals born in 2008 or later (who must be at least 18 years old) are no longer subject to educational threshold requirements for various positions; the company clearly states, “We believe that in the AI era, capability outweighs academic credentials.” The recruitment information specifies multiple benefits and requirements: newly hired employees can immediately receive an annual AI usage quota of at least 50,000 yuan; candidates must provide detailed insights on AI usage, usage records, representative cases, as well as resumes, proof of experience, investment research reports, and other relevant materials for preliminary AI evaluation.

From the recruitment positions, the Chief Artificial Intelligence Officer is required to lead the company’s AI integration and reshaping, with the core goal of significantly increasing productivity and reducing operational costs; the investment research positions cover five major areas: technological innovation, consumer, pharmaceuticals, manufacturing, and cyclical industries. New hires can gradually grow into fund managers, and the company additionally provides an AI tool usage quota equivalent to 50% of the base salary to assist investment research personnel in achieving “Token freedom.” Additionally, the recruitment also specifies character and capability requirements, including recognizing long-termism, a passion for challenging and fulfilling work, and having good stress resistance and self-drive.

It is reported that Zhiyu Zhi Shan’s 2026 investment strategy has been confirmed, and its planned “Interstellar Fleet” product line is already in operation, employing a trading system collaboratively developed by the investment research team and AI to form a “consensus” (one of the “AI Cybertron” sub-systems), with the core strategy being “Global Value Investment Strategy.” From the recruitment requirements, it is clear that the company has deeply embedded AI into core business processes such as investment research, risk control, operations, and marketing, and has allocated a special AI tool budget for employees. As early as 2023, the institution announced the use of “artificial intelligence robots” (AI) to independently manage its related asset management products.

He Li, the general manager of Zhiyu Zhi Shan, told the “Daily Economic News” reporter: “Our original intention was more about recruiting young talents from prestigious universities, such as the Youth Class of the University of Science and Technology of China, and the High School Affiliated to Renmin University of China; I have discussed this with relevant principals many times recently. We have now updated the recruitment notice, raising the threshold (from 16 years old) to 18 years old. The team itself is also very concerned about the psychological maturity of young candidates, and we sincerely apologize for any doubts raised (previously). In the future, we will continue to explore new paths for talent development in the AI era within a compliant framework.”

This recruitment by Zhiyu Zhi Shan seems to break educational and age restrictions, but in reality, it is advancing the “talent acquisition timeline,” with the core still being the competition for talents with AI capabilities. In fact, the war for AI talent in the private equity industry has long since begun, with leading institutions laying out plans to seize the high ground of AI technology. Currently, many private equity firms are actively recruiting machine learning researchers, neural network engineers, deep learning engineers, AI algorithm researchers, AI quantitative engineers, algorithm development engineers, and other related positions.

Quantitative giant Huanfang Quantitative is one of the first institutions in the private equity industry to lay out plans for artificial intelligence. It has already initiated talent recruitment in the AI field, fully exploring General Artificial Intelligence (AGI). According to information from its official website, Huanfang AI has created the deep learning training platform “Firefly No. 2” and developed a large-capacity, high-bandwidth file system (3FS) specifically designed for AI, which can support AI models to scale to multiple nodes, achieving large-scale parallel training. After Huanfang Quantitative nurtured DeepSeek, it significantly encouraged the entire private equity industry, pushing quantitative private equity to accelerate its embrace of AI technology, showcasing the wide recognition of AI development prospects in the financial sector.

In addition to Huanfang Quantitative, several hundred billion quantitative private equity firms are also continuing to make strides in the AI field. The hundred billion quantitative private equity firm Ming Shi Fund established the AI laboratory G-Lab in 2021 and launched the construction of computing hardware infrastructure in 2022, putting into operation the Ming Shi supercomputer Phase I “Andromeda” and Phase II “Perseus.” By 2025, it plans to further expand the “Constellation Program” supercomputer series and is currently recruiting AI scientists globally to promote AI technology innovation and application, exploring cutting-edge algorithms such as deep learning and machine learning.

In February 2025, the hundred billion quantitative private equity firm Kuan De Investment released recruitment information for the Kuan De Intelligent Learning Laboratory, focusing on general technology research and development, mainly hiring positions including AI researchers and AI engineers. At the beginning of the same year, Jiu Kun Investment partnered with the Microsoft team to publish a paper related to the AI field, successfully replicating the research results of DeepSeek-R1. It is reported that Jiu Kun Investment established its artificial intelligence laboratory relatively early, dedicated to cutting-edge AI technology research, exploring the application of general technologies in various scenarios, and conducting diversified research in multiple sub-fields to accelerate the landing of AI technology.

Industry insiders indicate that the empowerment of quantitative private equity by AI technology mainly manifests in four aspects: first, optimizing investment decisions by leveraging big data and machine learning to uncover potential market patterns; second, strengthening risk control by monitoring investment risks in real-time and dynamically adjusting investment portfolios; third, enhancing trading execution efficiency, effectively reducing trading costs; and fourth, improving operational efficiency by automating daily office tasks and releasing human capital costs.

Cover image source: AIGC

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Editor: Gao Jia