HireIntOS

HireIntOS transforms interview preparation into interview experience through personalized AI interviewers, adaptive coding challenges, and real-time feedback.

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HireIntOS - The Interview Simulator for Careers

Inspiration

As students, we've spent countless hours applying for internships and jobs. The problem isn't finding interview questions online - it's getting realistic interview practice before the real opportunity arrives.

A pilot wouldn't fly a plane without training in a simulator. We asked ourselves: why don't students have something similar for interviews?

That's how HireIntOS was born.

What it does

HireIntOS is an AI-powered interview platform that simulates a complete interview experience.

Students upload their resume and a job description, then interact with multiple AI interviewers that conduct:

  • HR Agent — Behavioral and culture-fit questions
  • Manager Agent — Leadership, prioritization, and situational scenarios
  • Technical Agent — Technical concepts and system design discussions
  • Coding Agent — Live coding interviews with progressive hints

The platform remembers previous sessions, adapts questions based on performance, and provides detailed feedback after every round.

One feature we're especially proud of is the coding interviewer. Instead of giving away solutions, it provides progressive hints just like a real interviewer would.

How we built it

We built HireIntOS using:

  • Google Gemini for AI-powered interview conversations
  • Google ADK for managing multiple interviewer agents
  • MongoDB Atlas and MongoDB MCP Server for interview history, candidate memory, and adaptive questioning
  • FastAPI for the backend
  • Next.js, React, and Tailwind CSS for the frontend
  • Monaco Editor for coding interviews
  • Web Speech API for voice interactions
  • Google Cloud Run for deployment

Challenges we ran into

One of our biggest challenges was making interviews feel personalized rather than repetitive.

We wanted the platform to remember what a student had already practiced, understand their strengths and weaknesses, and adjust future interviews accordingly. Using MongoDB MCP allowed our agents to access previous sessions and create a more realistic learning experience.

Another challenge was designing an AI coding interviewer that helps candidates think through problems without simply revealing answers.

Accomplishments that we're proud of

  • Built a multi-agent interview platform from scratch
  • Created personalized interview experiences based on resumes and job descriptions
  • Added candidate memory across sessions
  • Developed a hint-based coding interviewer
  • Integrated voice interaction and webcam support for a more realistic interview environment

What we learned

This project taught us a lot about building agent-based AI systems that work together and share context.

We also gained hands-on experience with:

  • Google ADK
  • Google Cloud
  • MongoDB MCP Server
  • Multi-agent orchestration
  • Adaptive AI experiences

Most importantly, we learned how to design AI systems that support learning rather than simply generating answers.

What's next for HireIntOS

We're excited to expand HireIntOS with:

  • More industry-specific interview tracks
  • Better performance analytics and progress tracking
  • Real-time communication and confidence feedback
  • Mock interview preparation tailored to specific companies

Our goal is simple:

Help students walk into interviews feeling prepared, confident, and ready to succeed.

Because careers deserve a simulator too.

Built With

  • docker
  • fastapi
  • google-adk
  • google-adk-(agent-development-kit)
  • google-artifact-registry
  • google-cloud
  • google-cloud-build
  • google-cloud-run
  • google-gemini
  • google-gemini-2.5-flash
  • mediapipe-face-mesh
  • monaco-editor
  • mongodb-atlas
  • mongodb-mcp-server
  • motor-(async-mongodb-driver)
  • next.js
  • next.js-15
  • pydantic
  • python
  • react
  • react-19
  • tailwind-css
  • typescript
  • web-speech-api
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