ByteDance, Alibaba and JD.com Launch 2027 Campus Hiring as AI Openings Surge 47.3%

The autumn campus recruitment season for the class of 2027 is underway, and several Chinese internet companies have opened their hiring processes. In early August, ByteDance, Alibaba and JD. com launched campus recruitment in succession. More than 70% of ByteDance's openings target technical and product roles, with new positions such as AI full-stack engineer and AI agent development added. At Alibaba, AI-related positions account for 80% of campus openings, while JD. com introduced AI-enabled interviews for the first time. According to data from the Maimai platform, newly posted campus AI positions rose 47.3% year on year from January to May 2026, with the penetration rate of AI positions rising from 26.41% to 37.56%.

Graduates from the classes of 2026 and 2027 have faced varying circumstances in their job searches. A 2027 undergraduate majoring in Chinese language and literature at Henan Normal University said she has submitted 40 to 50 resumes; 15 of the 25 positions she applied for were screened out, and only one or two have advanced to interviews. She previously provided marketing services for L'Oréal at BlueFocus and later handled overseas market operations at Hello, and is now interning at a Shanghai-based company focused on overseas expansion, using AI to generate advertising materials. The only major tech company interview she has secured is for an AIGC video creation position at Pinduoduo, where interviewers pressed her on model usage, workflows and how she handled failures and adjustments.

A 2027 master's student in software engineering at a Beijing 985 university has focused his applications on agent algorithm positions, with three or four interviews completed so far and results still pending. His observation is that among the 2026 campus AI openings at major tech companies, large-model algorithms, agent algorithms and AI infrastructure research and development are fiercely competitive, while the embodied-intelligence track faces less competition but explicitly requires matched internship experience. He said hiring demand for AI positions has changed between 2025 and 2026: the total number of openings has declined and requirements for coding ability have been adjusted.

A 2027 undergraduate majoring in computer science at a Shanghai university had originally planned a career in traditional back-end development, but shifted his target to AI application-layer or tool-chain roles given the high proportion of AI positions in big companies' campus recruitment. He has received two interview invitations so far: one for an AI product assistant role at a major company and one for an engineer position at an AI startup. To improve his competitiveness, he built a campus knowledge-base question-answering system using large models and experimented with using Copilot to assist with code writing during his internship.

A 2026 master's student in psychology at one of the five leading East China universities has officially joined a major company in a product role. She began interning as a sophomore and accumulated multiple experiences at Xiaohongshu, ByteDance and Tencent, including working on AI-related products at Tencent. She noted that during the 2025 campus recruitment cycle, the ratio of AI to non-AI positions was roughly 50-50, but in 2026 it has essentially shifted to 70-30. She tried applying for AI product positions in 2025 but did not receive an interview, and ultimately converted to full-time employment through a non-AI summer internship at a major company.

A 2027 master's student in software engineering at a 985 university began submitting resumes in July's early-batch round, sending more than 20 applications targeting large-model algorithms, agent algorithms and AI application development. He has interviewed with four or five companies so far, with two in later-stage processes. Having encountered AI early, he started learning machine learning in his junior year of undergraduate studies, participated in large-model projects during graduate school and interned at an AI startup. During interviews, he faced detailed questions about his RAG project, including document chunking, recall evaluation and data comparison, and some answers were incomplete. He subsequently revised his resume, removing projects he could not explain in depth, and now focuses his applications on the agent and large-model application directions with which he is more familiar.

The experiences of these graduates show that internship experience has become a key factor in job hunting, with interviewers generally focusing on specific project details and real-world deployment scenarios. Some respondents noted that a high proportion of AI positions does not necessarily mean more opportunities; job requirements are more granular and entry thresholds are rising.