JobTSU - Job That Suits You

AI-powered career recommendation platform designed for students, freshers, and early-career professionals who struggle to identify the right job roles based on their current skills.

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JobTSU – Job That Suits You 🎯

JobTSU is an AI-powered career recommendation platform designed for students, freshers, and early-career professionals who struggle to identify the right job roles based on their current skills.

Instead of generic advice, JobTSU analyzes resumes and professional profiles to:

  • Recommend realistic job roles
  • Identify skill gaps
  • Suggest clear learning paths
  • Improve resume and LinkedIn ATS visibility

🚀 Inspiration

Students and freshers often face:

  • Confusion about which job roles they are actually eligible for
  • Overwhelming and vague career advice online
  • No clarity on what to learn next to become job-ready

JobTSU was built to solve this exact problem by acting like a technical recruiter + career advisor, powered by AI.

🧠 What It Does

JobTSU takes structured professional inputs and produces actionable career insights.

Inputs

  • Resume (PDF / text)
  • LinkedIn profile data
  • Optional: GitHub, portfolio links

Outputs

  1. Eligible Now Jobs

    • Job roles the user can apply for immediately
    • Match percentage
    • Matching skills

  2. Eligible After Learning Jobs

    • Roles achievable after targeted upskilling
    • Missing skills clearly listed

  3. Skill Gap Analysis

    • Core concepts
    • Tools & frameworks
    • Nice-to-have skills

  4. Learning Path Recommendation

    • High-impact skills only
    • Industry-aligned topics
    • Clear justification for each skill

  5. Resume ATS Suggestions

    • Keyword gaps
    • Role-specific improvements
    • No fake claims

  6. LinkedIn Profile Suggestions

    • Headline optimization
    • Summary restructuring
    • Skill alignment improvements

🛠️ How We Built It

Tech Stack

  • Frontend: React, Next.js
  • Backend: Node.js, Express
  • Database: Firebase Firestore
  • AI Layer: Google Gemini (LLM)
  • Parsing: Resume & profile text normalization

Architecture Highlights

  • Skill extraction and normalization pipeline
  • Job-role mapping using industry skill expectations
  • Token-optimized prompt design
  • Structured JSON-compatible AI outputs
  • Separation of reasoning and presentation layers

⚙️ Challenges We Ran Into

  • Preventing hallucinated skills or experience
  • Designing prompts that behave like a real recruiter
  • Keeping AI outputs structured and predictable
  • Reducing token usage while maintaining accuracy
  • Avoiding generic career advice

🏆 Accomplishments We’re Proud Of

  • Built a production-grade career advisor, not a chatbot
  • Accurate job role matching for early-career users
  • Clear distinction between eligible now vs after learning
  • Highly structured outputs suitable for real users
  • Scalable architecture for future features

📚 What We Learned

  • Prompt engineering for decision-making systems
  • Skill normalization and job taxonomy mapping
  • Designing AI systems with constraints and realism
  • Importance of structure over creativity in career tools

🔮 What’s Next for JobTSU

  • Live job listing integration (LinkedIn, Internshala, etc.)
  • Company-specific resume optimization
  • Interview preparation based on target roles
  • Job application tracking
  • Portfolio and GitHub quality analysis
  • Personalized weekly learning roadmap

👤 Built By

Atharva Kaplay
Student | AI & Career Tech Builder
Focus: Robotics, Embedded Systems, AI Systems

📌 Disclaimer

JobTSU does not guarantee placements.
All recommendations are based on skill-role alignment and current industry expectations.

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