Higher vocational education serves as the cornerstone for cultivating highly skilled talents. However, its internship and employment phase has long been plagued by systemic challenges such as low efficiency in person-job matching and insufficient momentum for students’ career development. The emergence of large artificial intelligence (AI) models represented by DeepSeek has offered a new possibility to address this dilemma, shifting from “instrumental matching” to “ecological empowerment.” Adopting literature analysis and framework construction methods, the study proposes that DeepSeek’s application effectiveness manifests in three progressive levels: the precise matching layer as an information intermediary, the capacity empowerment layer as an intelligent mentor, and the developmental empowerment layer as a career partner. Research indicates that by constructing a dynamic and closed-loop support system, DeepSeek not only improves job search efficiency but also stimulates students’ endogenous motivation, realizing a fundamental transformation from passive adaptation to proactive development. This provides a solution with both theoretical depth and practical value for promoting the high-quality development of vocational education.