AI-Powered Chatbot for Job Interview Preparation

Background

The traditional interview process often lacks comprehensive evaluation of key traits like behavior, communication, empathy, leadership, and problem-solving. Candidates are frequently left unprepared due to the absence of realistic mock interviews and tailored resources. The HR Interview Prep Chatbot project was launched to address these challenges, providing an immersive, personalized preparation experience that empowers job seekers with the confidence and skills to excel.

Objective

This project aimed to:

1. Develop a platform that enables job aspirants to participate in mock interviews and identify areas for improvement.
2. Explore the potential of large language model (LLM)-based applications in human development.
3. Enhance participants’ skills in NLP, LLM-based applications, prompt engineering, and retrieval-augmented generation (RAG).

Approach

The team tackled the problem through a multi-phase approach:

1. Data Collection: Collected a wide variety of HR interview questions, appropriate and inappropriate responses, and contextual requirements from online platforms like Indeed, LinkedIn, and Glassdoor for the top 10 roles with frequent job postings.
2. Role Identification: Collaborated with HR professionals and soft-skills trainers to identify the top three roles most suitable for mock interview preparation.
3. Pipeline Design: Built an application that interacts with users, conducts mock interviews, collects responses, preprocesses inputs, invokes evaluation models, and delivers personalized feedback and recommendations.
4. Modeling: Identified suitable models and explored LLM techniques, such as fine-tuning and retrieval-augmented generation (RAG), to design the evaluation and recommendation pipeline.

Results and Impact

The project delivered an AI-powered chatbot capable of conducting realistic mock interviews for HR-focused roles, including teaching, leadership, and sales. Key outcomes include:

• Enhanced Preparedness: Candidates received detailed feedback on behavioral traits, communication, empathy, leadership, and problem-solving skills.
• Scalability: The platform is scalable to diverse job roles beyond the initial scope.
• Skill Development: Participants gained hands-on experience in NLP, prompt engineering, and LLM-based applications.

Future Implications

This project sets the stage for broader applications of LLMs in professional development and human resource technology. Future research could extend the chatbot’s capabilities to include domain-specific roles and integrate advanced AI-driven insights to adapt to evolving industry requirements. Additionally, its success highlights the potential for AI to democratize access to high-quality interview preparation resources, fostering global employability.