AI Mock Interviewer

Inspiration

Preparing for technical interviews is a highly stressful experience for developers. Most preparation tools are static. We wanted to build an interactive, conversational platform that simulates a real-world engineering interview while evaluating technical soundness on the fly.

What it does

AI Mock Interviewer is a fully responsive simulation platform. A candidate enters their target Job Profile and Company Name. The system then generates a context-aware, step-by-step interview experience. It evaluates user text inputs using an integrated conversational agent and provides instant technical simulation feedback.

How we built it

• Frontend: Built using HTML5, CSS3, and JavaScript to manage smooth UI updates and chat behaviors.
• Backend: Powered by a Python Flask server designed to manage dynamic route states without blocking the user flow.
• AI Core Framework: Conceptualized around GPT-5.6 for conversational flow management and OpenAI Codex for technical code analysis, with an active free-tier AI integration layer for full responsiveness.

Challenges we faced

Handling cross-origin resource sharing (CORS) directly through native Flask headers without relying on heavy external packages, and managing real-time response generation dynamically.

Built With

• gpt-5.6
• html5
• javascript
• openaicodex
• python