HireGenie AI

Inspiration

Many students and job seekers apply to dozens of jobs but still fail because their resume is not ATS-friendly and they don’t know what interview questions will be asked for a specific role. Most tools provide generic advice, but real improvement requires personalized feedback based on the resume and job description.

That inspired me to build HireGenie AI, a complete career assistant powered by Gemini 3.

What it does

HireGenie AI analyzes a user's Resume and Job Description and generates:

ATS Match Score (0–100) with missing keyword detection
Keyword Match Report (matched vs missing skills)
Resume Improvement Suggestions
Resume Summary Rewrite
Skill Gap / Weak Areas Report with chart-style visualization
Role-specific Interview Question Generator
Mock Interview Mode
Answer Evaluation with scoring and ideal rewritten answers
Job Search Assistant suggesting top relevant job openings

It also includes a Career Chatbot tab where users can ask career-related questions such as:

how to improve resume
what skills to learn next
roadmap for full-stack/backend roles
project recommendations

How I built it

Built the UI using React + TypeScript
Used Gemini 3 API as the core reasoning engine
Implemented prompt-routing logic based on selected mode (ATS, Interview, Weak Areas, Job Search, etc.)
Used structured output formatting for clean reports and PDF-friendly output

Challenges I ran into

Maintaining consistent output formatting (tables, headings, structured sections)
Designing prompts that produce reliable JSON outputs for charts
Ensuring the results are ATS-friendly and not generic