分析全球提示工程岗位需求，揭示其独特技能要求。
Prompt Engineer: Analyzing Hard and Soft Skill Requirements in the AI Job Market
- 基于20,662份领英职位数据，识别提示工程师核心能力。
- 提示工程岗位占比不足0.5%，但需AI知识、提示设计等四类技能。
- 适合求职者、企业及教育机构了解新兴岗位趋势。
大型语言模型（LLMs）的兴起催生了一种新职业：提示工程师。尽管该职位关注度上升，但我们对其所需技能及普及程度仍不明确。本文基于领英平台的数据，对全球20,662个职位招聘广告进行了分析，其中包含72个提示工程师岗位。研究发现，提示工程岗位占比低于0.5%，但具有独特的技能组合：需要人工智能知识（22.8%）、提示设计技能（18.7%）、良好沟通能力（21.9%）以及创造性解决问题能力（15.8%）。这些要求显著区别于数据科学家和机器学习工程师等成熟角色。研究结果有助于求职者、雇主和教育机构更清晰地理解这一新兴领域。
原文摘要 · Abstract (English)
The rise of large language models (LLMs) has created a new job role: the Prompt Engineer. Despite growing interest in this position, we still do not fully understand what skills this new job role requires or how common these jobs are. In this paper, we present a data-driven analysis of global prompt engineering job trends on LinkedIn. We take a snapshot of the evolving AI workforce by analyzing 20,662 job postings on LinkedIn, including 72 prompt engineer positions, to learn more about this emerging role. We find that prompt engineering is still rare (less than 0.5% of sampled job postings) but has a unique skill profile. Prompt engineers need AI knowledge (22.8%), prompt design skills (18.7%), good communication (21.9%), and creative problem-solving (15.8%) skills. These requirements significantly differ from those of established roles, such as data scientists and machine learning engineers. Our findings help job seekers, employers, and educational institutions in better understanding the emerging field of prompt engineering.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。