JOBsy

byRamya Ramamurthy

# JOBsy – AI-Powered Job Search Copilot ## Project Overview Build a modern SaaS web application called **JOBsy**. JOBsy is an AI-powered job search assistant that automates and simplifies the entire job application process. The platform should: * Store multiple resume versions. * Build a master professional profile. * Discover relevant jobs automatically. * Analyze each job description. * Tailor the best resume for every application. * Generate cover letters. * Ask the user for approval using a swipe interface. * Apply (where supported and with user approval). * Track every application automatically. * Update application statuses from user actions and connected email (with permission). * Provide analytics and insights. The design should feel modern, minimal, and premium (similar to Linear, Notion, Stripe, or Vercel). --- # Tech Stack ## Frontend * Next.js (App Router) * TypeScript * Tailwind CSS * shadcn/ui * Framer Motion * React Query * Zustand ## Backend * FastAPI (Python) * PostgreSQL * SQLAlchemy * Alembic * Redis * Celery ## AI * OpenAI Responses API * Embeddings * pgvector * RAG architecture ## Authentication * Clerk or Auth.js ## Storage * S3-compatible storage * PostgreSQL --- # Core Modules ## 1. Authentication Support: * Google Login * GitHub Login * Email Login --- ## 2. Dashboard The dashboard should show: * Applications Sent * Saved Jobs * Resume Versions * Interviews * Rejections * Offers * Upcoming Interviews * Weekly Analytics * Match Rate * Response Rate --- ## 3. Master Profile Allow users to build a complete professional profile. Include: Personal Information * Name * Email * Phone * LinkedIn * GitHub * Portfolio Education Experience Projects Achievements Publications Certifications Skills Languages Preferred Locations Expected Salary Visa Status Notice Period Everything entered here becomes the "single source of truth." --- ## 4. Resume Vault Users can upload multiple resumes. Examples: * AI Resume * Backend Resume * Full Stack Resume * ML Resume * Research Resume Each resume should: * be parsed * indexed * searchable * editable Store: * DOCX * PDF --- ## 5. Resume Intelligence When given a Job Description: The AI should: Extract: * Skills * Responsibilities * Experience Required * ATS Keywords * Soft Skills * Preferred Skills Then: * Select the best resume automatically. * Rewrite bullet points. * Reorder sections. * Highlight relevant projects. * Keep everything truthful. * Never invent experience. * Improve ATS compatibility naturally. Output: * Tailored Resume (PDF) * Tailored Resume (DOCX) * ATS Match Score * Summary of changes Example: Added: * Kubernetes * LangChain * AWS Lambda Removed: * Android Project Modified: * Backend API Project now emphasizes REST APIs and scalability. --- ## 6. Cover Letter Generator Generate a customized cover letter using: * Company * Job Description * Resume * User Profile --- ## 7. Job Discovery Engine Automatically search jobs from supported sources. Examples: * Greenhouse * Lever * Ashby * Company Career Pages * RemoteOK * Wellfound * Other public job boards Avoid duplicates. Run scheduled searches. Allow filters: * Remote * Hybrid * Onsite * Visa Sponsorship * Salary * Country * Experience Level * Job Type --- ## 8. AI Job Matching Every discovered job should receive a match score. Example: Google - 95% SAP - 91% Amazon - 88% Bosch - 84% Factors: * Skills * Experience * Education * Salary * Location * Visa * Preferred Stack Display: Why this score? Example: Strong Match: ✔ Python ✔ FastAPI ✔ Docker Missing: ✖ Terraform ✖ Kafka --- ## 9. Swipe Interface Create a Tinder-like interface. Each card should display: Company Role Location Salary Match Score Required Skills Buttons: ❤️ Apply 👎 Ignore ⭐ Save 📄 View JD 📈 Why Match? Swiping right means: Generate Resume Generate Cover Letter Prepare Application Ask for confirmation --- ## 10. Auto Apply Support semi-automated applications where feasible. Workflow: Prepare application. If additional questions exist: Pause. Ask user. Generate suggested answers. Continue only after user approval. Never submit an application without explicit confirmation. --- ## 11. Application Tracker Maintain a structured database instead of Excel. Fields: Serial Number Company Name Job Title Job Description Application URL Resume Version Cover Letter Date Applied Current Status Recruiter Name Notes Interview Dates Portal Used Statuses: Saved Ready Applied Assessment Phone Screen Technical Interview Manager Interview HR Interview Offer Rejected Withdrawn Accepted Declined --- ## 12. Automatic Status Updates If email integration is enabled: Detect: Interview Invitations Rejections Offers Assessment Requests Automatically update the tracker. Never modify data without showing the detected update to the user first. --- ## 13. Analytics Display: Applications per Week Response Rate Interview Rate Offer Rate Average Match Score Top Skills Rejected Reasons (if known) Interactive charts. --- ## 14. AI Assistant Include an AI chatbot. Examples: "Find me remote AI Engineer jobs." "Tailor my resume for this job." "What skills am I missing?" "Prepare interview questions." "Generate follow-up email." --- ## 15. Resume Version History Every tailored resume becomes a version. Allow: Compare versions Restore versions Download View changes --- ## 16. Notifications Notify users when: New matching jobs appear Resume tailoring completes Application submitted Interview detected Offer detected --- ## UI Theme Modern. Minimal. Premium. Dark mode first. Rounded corners. Smooth animations. Excellent typography. Glassmorphism where appropriate. Use shadcn/ui components. --- ## Database Schema Tables: Users Profiles Experiences Projects Skills Education Resumes ResumeVersions Jobs Companies Applications ApplicationEvents CoverLetters Emails InterviewRounds Notifications AutomationTasks --- ## AI Rules The AI must: * Never fabricate experience. * Never claim skills the user does not possess. * Tailor wording without lying. * Explain every resume modification. * Keep outputs ATS-friendly. * Request clarification when information is insufficient. --- ## Future Features * Chrome Extension * LinkedIn Helper * Salary Prediction * Referral Suggestions * Interview Coach * Portfolio Generator * Networking Assistant * Calendar Integration * Mobile App * Voice Assistant --- ## Deliverables Generate: 1. Complete system architecture. 2. Folder structure. 3. Database schema. 4. API design. 5. UI wireframes. 6. Backend implementation. 7. Frontend implementation. 8. AI workflow. 9. Authentication flow. 10. Deployment guide. 11. Docker configuration. 12. CI/CD pipeline. 13. Production-ready code with comments. Build the project incrementally, feature by feature, using clean architecture, scalable design patterns, and production-quality code. Before implementing each major module, explain the design decisions and propose the project structure for that module.