advanced ~35 hours

AI Interview Coach

Voice-enabled interview practice agent with real-time feedback, scoring, and personalized improvement plans.

Overview

Voice-enabled interview practice agent with real-time feedback, scoring, and personalized improvement plans.

Architecture

A advanced-level project using Python, OpenAI Realtime API, Whisper, React. The architecture follows a modular design with clear separation between data ingestion, AI processing, and user interface layers.

Tech Stack

Python · OpenAI Realtime API · Whisper · React

Features

Voice interaction
Real-time feedback
Score tracking
Personalized coaching

Resume Points

Built voice-enabled AI interview coach with real-time speech processing
Designed evaluation rubric with automated scoring across 5 dimensions

Interview Questions

How would you architect this project for production?

Discuss: API design, error handling, observability (tracing, logging), cost optimization (caching, model routing), security (input validation, rate limiting), and deployment strategy (Docker, CI/CD, auto-scaling).

What were the biggest challenges building this?

Focus on AI-specific challenges: prompt reliability, hallucination handling, latency optimization, cost management, and evaluation of AI output quality.