Software and AI developer focused on building full-stack web applications, backend services, and AI-integrated workflows.

An AI-powered HRMS and Applicant Tracking System designed to streamline recruitment, candidate evaluation, and workforce management.

🔗 GitHub Repository  |  🌐 Live Application

Recruitment workflows typically involve manually reviewing resumes, evaluating candidates against job requirements, managing candidate stages across disconnected tools, and handling interview coordination without centralized data.

BluHire-AI consolidates candidate tracking, resume screening, voice interview evaluation, and workforce records into a single system, using AI services to assist recruiters with candidate assessment and data retrieval.

• AI Resume Screening & Parsing: Automated text extraction from PDF and DOCX files (pdfplumber, PyMuPDF, python-docx) paired with an AI screening service to evaluate candidate skills and qualification matching against job descriptions.
• RAG Knowledge Base: Document ingestion and semantic search using vector embeddings (sentence-transformers) and MongoDB Atlas Vector Search to answer queries and retrieve organizational documentation.
• AI HR Copilot: Conversational assistant built with FastAPI and OpenRouter supporting streaming responses for HR inquiries and operational assistance.
• Recruitment Pipeline & Candidate Workspace: Multi-stage candidate tracking with interactive stage transitions, a candidate drawer for profile inspection, and skill-matching analysis.
• Voice Interview & Evaluation: Voice response capture with transcription via OpenAI Whisper and automated evaluation across technical competency, problem-solving, and recommendations.
• Performance Management: Structured performance tracking, evaluation cycles, skill gap insights, and automated learning plan generation.
• Role-Based Access Control & Async Processing: JWT authentication and role-based access for Admins, HR Managers, Recruiters, and Employees, with BullMQ and Redis queues handling asynchronous processing tasks.

flowchart TD
    A[Next.js Frontend] -->|REST / Streaming| B[Node.js + Express API]
    B --> C[MongoDB]
    B --> D[BullMQ + Redis Queue]
    B -->|AI Requests| E[FastAPI AI Service]

    D --> E

    E --> F[OpenRouter LLM API]
    E --> G[OpenAI Whisper Audio Transcription]
    E --> H[Sentence Transformers Embeddings]

    E --> I[Document Processing]
    I --> J[PDF / DOCX Parsers]

    E --> K[MongoDB Atlas Vector Search]

• Framework: Next.js 15, React 19, TypeScript
• Styling & UI: Tailwind CSS, Framer Motion, Lucide Icons
• State & Data Fetching: TanStack React Query, Zustand
• Data Visualization: Recharts

• Core: Node.js, Express.js, TypeScript
• Queue & Caching: BullMQ, Redis (ioredis)
• Authentication & Security: JWT, bcrypt
• File Handling: Multer

• Service: Python, FastAPI, Uvicorn, Pydantic
• Speech-to-Text: OpenAI Whisper
• Embeddings: Sentence Transformers
• LLM Gateway: OpenRouter API
• Document Extraction: PyMuPDF, pdfplumber, python-docx

• Database: MongoDB, Mongoose
• Vector Search: MongoDB Atlas Vector Search

• Hosting: Vercel (Frontend)
• Version Control: Git, GitHub

• Full-stack web application development with Next.js, TypeScript, and Node.js
• AI integration, RAG systems, and vector search workflows
• Backend API architecture and asynchronous task processing

• LinkedIn: linkedin.com/in/dhanush-maddila-6574aa252
• GitHub: github.com/thedhanush0905
• Email: dhanushmaddila0905@gmail.com