Career Coach is an AI-powered career reflection tool that helps job seekers gain insight into their strengths, gaps, and potential next steps. It analyzes your resume and self-reflection responses to generate a personalized career coaching report and matching job opportunities — just like working with a career consultant, but automated and scalable.

• Upload your PDF resume
• Redact PII (Personally Identifiable Information) by selecting text and right-clicking - redacted text is completely removed before analysis
• Answer 6 personalized career reflection questions
• Receive an AI-generated coaching report including:
  • Career direction (Pivot, Grow, Reinvent)
  • Key strengths and skills
  • Gaps and improvement areas
  • Actionable recommendations
  • Suggested job titles and industries
• Get matching job opportunities that align with your:
  • Career direction and goals
  • Current skills and experience
  • Areas for growth
  • Each job match includes:
    • Job title and description
    • Why it matches your profile
    • Your matching skills
    • Skills you need to develop

Try it now: career-coach-alpha.vercel.app
Resume parsing and coaching powered by FastAPI on Render

No personal data is stored — resume and answers are used only during the session.

[ Vercel Frontend ]
        |
    fetch()
        ↓
[ Render Backend (FastAPI) ]
        ├─ /upload_resume → parse PDF with pdfplumber
        ├─ /questions → loads shared JSON questions
        ├─ /analyze → merges resume + answers, calls OpenAI API
        └─ /find_jobs → matches coaching summary with job opportunities

• Shared logic (resume parsing, prompt formatting) is used by both CLI and backend
• All user input is processed in-memory; nothing is stored long-term
• PII redaction happens client-side before analysis to ensure privacy
• Job matching uses the coaching summary to find relevant opportunities

# 1. Clone the repo
git clone https://github.com/velde/career-coach.git
cd career-coach

# 2. Set up backend
cd backend
python -m venv venv
source venv/bin/activate
pip install -r ../requirements.txt
touch .env  # and add your OPENAI_API_KEY

# Run backend
uvicorn app:app --reload --port 8000

# 3. Set up frontend
cd ../frontend
npm install
npm start

• Allow exporting report to PDF
• Add user login to save sessions
• Use fine-tuned models for deeper insight
• Add more job matching sources
• Improve job matching accuracy with feedback

This project is licensed under the MIT License - see the LICENSE file for details.

The MIT License is a permissive license that is short and to the point. It lets people do anything they want with your code as long as they provide attribution back to you and don't hold you liable.

Key permissions under MIT License:

• Commercial use
• Modification
• Distribution
• Private use

For more information about the MIT License, visit choosealicense.com/licenses/mit/.