# AI Interview Agent

> A conversational AI system for interview simulation — it runs a live interview and returns real-time structured scoring and feedback, turning an open-ended conversation into measurable, comparable signal.

- Canonical: https://hasib.tech/work/interview-agent
- Role: AI Engineer — Backend
- Year: 2025—26
- Category: Conversational AI
- Stack: FastAPI, LangGraph, OpenAI, Structured Output Parsing, WebSockets
- Mode: Live conversational interview
- Output: Real-time structured scoring

An interview is an open-ended conversation, but the value of one is in the
structure you can pull back out: how a candidate reasoned, where they hesitated,
what they actually demonstrated. This agent runs the conversation and produces
that structure in real time.

## Scoring a conversation as it happens

The system conducts a live interview and emits **real-time structured scoring
and feedback** rather than a single verdict at the end. The hard part is
reliability — turning free-form model output into a consistent, comparable
schema — which I handle with structured output parsing so every response maps
cleanly onto the scoring model.

## Orchestrated, not prompted

The interview flow is orchestrated with LangGraph as explicit stages — ask,
follow up, evaluate — over a FastAPI backend with a streaming channel for the
live exchange. Treating the dialogue as a graph keeps it controllable instead
of letting one long prompt drift.