Full Stack SaaS Developer for AI-Recruitment
Budget: ₹12,500 – ₹37,500 INR
AI-Powered Recruitment Platform | Full Stack SaaS Application with AI/ML Integration
Developed a complete AI-powered recruitment and job recommendation platform designed to streamline the hiring process for students, recruiters, and administrators. The platform combines modern full-stack development, machine learning, analytics, and real-time workflow management into a scalable SaaS-style solution.
Key Features & Functionality:
• Multi-role system with dedicated dashboards for Students, Recruiters, and Admins using secure JWT authentication and role-based access control (RBAC).
• AI-powered resume analysis and intelligent job matching using Python Flask microservices, spaCy NLP, TF-IDF vectorization, and cosine similarity algorithms.
• Resume parsing engine capable of extracting:
* Skills
* Education details
* Organizations
* Experience information
from PDF, DOCX, and text-based resumes.
• Smart candidate-job fit score calculation that ranks candidates and jobs based on extracted skills and relevance scoring.
• Recruiter workflow automation including:
* Job posting and management
* Applicant tracking system (ATS)
* Interview scheduling
* Candidate filtering
* Skill gap analysis
* Recruiter analytics dashboard
• Student dashboard with:
* Personalized job recommendations
* Application tracking
* Resume upload and analysis
* Match score visualization
* Analytics and insights
• Admin panel for complete platform control:
* User management
* Job moderation
* Analytics monitoring
* Activity management
• Integrated Google Calendar and meeting scheduling system for automated interview management.
• Built monitoring and observability infrastructure using Grafana and Spring Boot Actuator for:
* API monitoring
* JVM metrics
* p95/p99 latency analysis
* Connection pool tracking
* System health monitoring
• Performance optimization using:
* Redis caching
* Batch ML processing
* React Query caching
* Gunicorn worker/thread tuning
Technology Stack:
Backend:
Java, Spring Boot, Spring Security, JWT, PostgreSQL, Redis
Frontend:
React.js, Tailwind CSS, React Query, Recharts, Framer Motion
AI/ML:
Python, Flask, spaCy, Scikit-learn, TF-IDF, NLP, Cosine Similarity
Monitoring & Deployment:
Grafana, Gunicorn, Spring Actuator, Git/GitHub
This project demonstrates expertise in building scalable, production-oriented full-stack applications with AI integration, workflow automation, analytics, and modern software architecture.
Developed a complete AI-powered recruitment and job recommendation platform designed to streamline the hiring process for students, recruiters, and administrators. The platform combines modern full-stack development, machine learning, analytics, and real-time workflow management into a scalable SaaS-style solution.
Key Features & Functionality:
• Multi-role system with dedicated dashboards for Students, Recruiters, and Admins using secure JWT authentication and role-based access control (RBAC).
• AI-powered resume analysis and intelligent job matching using Python Flask microservices, spaCy NLP, TF-IDF vectorization, and cosine similarity algorithms.
• Resume parsing engine capable of extracting:
* Skills
* Education details
* Organizations
* Experience information
from PDF, DOCX, and text-based resumes.
• Smart candidate-job fit score calculation that ranks candidates and jobs based on extracted skills and relevance scoring.
• Recruiter workflow automation including:
* Job posting and management
* Applicant tracking system (ATS)
* Interview scheduling
* Candidate filtering
* Skill gap analysis
* Recruiter analytics dashboard
• Student dashboard with:
* Personalized job recommendations
* Application tracking
* Resume upload and analysis
* Match score visualization
* Analytics and insights
• Admin panel for complete platform control:
* User management
* Job moderation
* Analytics monitoring
* Activity management
• Integrated Google Calendar and meeting scheduling system for automated interview management.
• Built monitoring and observability infrastructure using Grafana and Spring Boot Actuator for:
* API monitoring
* JVM metrics
* p95/p99 latency analysis
* Connection pool tracking
* System health monitoring
• Performance optimization using:
* Redis caching
* Batch ML processing
* React Query caching
* Gunicorn worker/thread tuning
Technology Stack:
Backend:
Java, Spring Boot, Spring Security, JWT, PostgreSQL, Redis
Frontend:
React.js, Tailwind CSS, React Query, Recharts, Framer Motion
AI/ML:
Python, Flask, spaCy, Scikit-learn, TF-IDF, NLP, Cosine Similarity
Monitoring & Deployment:
Grafana, Gunicorn, Spring Actuator, Git/GitHub
This project demonstrates expertise in building scalable, production-oriented full-stack applications with AI integration, workflow automation, analytics, and modern software architecture.