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2024·Full-stack engineer

Real-Time AI Interview

WebRTC interview simulator that streams candidate audio to GPT evaluators for live feedback, scoring, and transcripts.

Stack

Next.js,Node/WebSocket,Redis,OpenAI Realtime,PostgreSQL

Timeline

2024

Impact

  • Reduced interviewer prep time by 40%
  • Under 300ms round-trip latency for feedback
Demo request

Context & Goals

Interview coaching platforms often lack live, contextual feedback. This project delivers a browser-based interviewer that listens, scores, and surfaces coaching tips in real time without sacrificing privacy or stability.

Architecture Overview

  • Client: Next.js front-end with WebRTC publisher, noise gating, and timeline UI.
  • Signaling: Node server establishing WebRTC sessions, handling TURN/STUN negotiation, and streaming audio frames to evaluators.
  • Inference layer: GPT-based evaluators running in parallel, enriching transcripts with rubric checks (communication, technical depth, empathy).
  • Storage: Redis for transient session data, PostgreSQL for final reports, highlights, and improvement suggestions.

Highlights

  • Built adaptive scoring that adjusts rubrics mid-session based on candidate responses and job role.
  • Implemented safe-words and privacy controls; sessions can redact sensitive topics before saving transcripts.
  • Added playback controls that pair video segments with constructive coaching cards.

Next Steps

  • Expand to support collaborative interviewer panels with shared annotations.
  • Integrate HRIS exports to close the loop on performance tracking.