The advancements in systems deploying large language models (LLMs), as well as improvements in their ability to act as agents with predefined templates, provide an opportunity to conduct qualitative, individualized assessments, creating a bridge between qualitative and quantitative methods for candidates seeking career progression. In this paper, we develop a platform that allows candidates to run AI-led interviews to assess their current career stage and curate coursework to enable progression to the next level. Our approach incorporates predefined career trajectories, associated skills, and a method to recommend the best resources for gaining the necessary skills for advancement. We employ OpenAI API calls along with expertly compiled chat templates to assess candidate competence. Our platform is highly configurable due to the modularity of the development, is easy to deploy and use, and available as a web interface where the only requirement is candidate resumes in PDF format. We demonstrate a use-case centered on software engineering and intend to extend this platform to be domain-agnostic, requiring only regular updates to chat templates as industries evolve.

翻译：部署大语言模型的系统不断进步，以及其作为具备预定义模板的智能体能力的提升，为寻求职业发展的候选人提供了进行定性化、个性化评估的机会，从而在定性与定量方法之间架起桥梁。本文开发了一个平台，允许候选人通过人工智能主导的面试来评估其当前职业阶段，并策划课程学习以推动其向更高层次发展。我们的方法整合了预定义的职业发展路径、相关技能以及一套推荐最佳学习资源以获取晋升所需技能的方法。我们利用OpenAI API调用与专家编制的对话模板来评估候选人的能力。由于采用模块化开发，该平台具有高度可配置性，易于部署和使用，并以网页界面形式提供，唯一要求是候选人提交PDF格式的简历。我们展示了以软件工程为核心的用例，并计划将该平台扩展为领域无关的系统，仅需随行业演变定期更新对话模板即可。