Divya · MERN Stack Developer · 4+ yrs
Mid-LevelAbout Divya
Divya is a Full Stack Developer building 8 AI-driven projects spanning Sales Automation + Project Development Automation + RAG-Based AI Chatbot + Intelligent Employee Prospecting + CSMS Crime Scene Mgmt + E-commerce Electronics + Cell Tracing + Puravida Event Mgmt. Specializes in AI + LangChain + Jira + GitHub + RAG across Sales + DevOps…
4+ years of commercial experience in
Skills(45)
Why hire Divya?
Sales Automation — leads from Google/LinkedIn/Upwork
Project Dev Automation — Jira + GitHub + test cases
Intelligent Employee Prospecting — HR recruitment automation
CSMS Crime Scene Mgmt — Government 3-role
Built 8 AI projects spanning Sales + Project Dev + RAG + HR + Govt + E-commerce + Cell + Event
Project highlights(8)
Sales Automation Process – Full Stack Developer
- End-to-end automated sales outreach — extracting leads from Google, LinkedIn, Upwork, Freelancer, government portals and partner sites based on Ideal Customer Profile (ICP), generating personalised email templates and analysing campaign metrics.
- Developed Python scripts for multi-platform data extraction.
- Processed and cleaned data into Excel for outreach use.
- Built dynamic personalised email templates and automated campaign launching.
- Built analytics dashboards for lead generation, open rates and hot-lead identification.
- Applied AI/ML for lead scoring and targeting precision.
Key outcomes:
Automated multi-platform lead generation with personalised email outreach and AI-based lead scoring.
Project Development & Planning Automation – Full Stack Developer
- Automation for Jira ticket generation, GitHub repo structuring and test-case creation from project requirement documents.
- Parsed project requirement documents (PDF, Word, text) and auto-created Jira tickets.
- Built scripts to create GitHub repos structured by Jira tickets, with branch creation per ticket and initial commits.
- Designed a system to generate test cases automatically linked to Jira user stories.
- Used Gemini LLM and Groq APIs for content generation.
Key outcomes:
Auto-generated Jira tickets, GitHub repos and linked test cases from natural-language requirements.
RAG-Based AI Chatbot – Full Stack Developer
- AI-powered document assistant enabling instant Q&A from uploaded PDFs using Retrieval-Augmented Generation (RAG) with LangChain, Groq LLaMA and FAISS vector search.
- Developed core backend logic using Python + LangChain for LLM orchestration.
- Integrated Groq's LLaMA model for context-aware responses.
- Implemented FAISS vector search for efficient document indexing and semantic retrieval.
- Designed Streamlit UI for seamless user interaction.
- Enabled PDF upload, parsing and chunking for large documents in real time.
Key outcomes:
Shipped RAG chatbot with LangChain + Groq LLaMA + FAISS for context-aware document Q&A.
Intelligent Employee Prospecting & Engagement Platform – Full Stack Developer
- AI-powered HR recruitment automation — extracting candidate data, automating outreach, scheduling interviews and generating LLM-based interview reviews.
- Built backend services in Python + Flask for data extraction, message sending and calendar integration.
- Built React.js frontend for visualising candidate data and managing interview pipelines.
- Automated candidate data extraction from public directories and ICP-aligned websites.
- Integrated Google Calendar API for auto-Meet link creation.
- Used LLaMA 3.2 to analyse interview notes and generate structured candidate review reports.
Key outcomes:
Automated candidate sourcing + outreach + interview scheduling with LLM-generated interview reviews.
CSMS — Crime Scene Management System – Full Stack Developer
- Government project with three roles — officer (on-site evidence collection), deputy (district-level reporting) and admin (state-level reporting). Officers fill evidence forms and upload media, then design reports using emudhra digital-signature service.
- Implemented role-based access for officers, deputies and admin.
- Managed application state using Redux + Context API.
- Integrated RESTful APIs for dynamic content rendering.
- Used SQLite for offline-capable persistent storage in field conditions.
Key outcomes:
Shipped offline-capable government crime-management app with emudhra digital signing and three-role RBAC.
Industry experience
AI / ML Platform
5 projects- •Sales Automation Process— Full Stack DeveloperPython · Flask · MySQL · Pandas +2
- •Project Development & Planning Automation— Full Stack DeveloperPython · Flask · React · Gemini LLM +2
- •RAG-Based AI Chatbot— Full Stack DeveloperGroq API · LangChain · LLaMA 3 · HuggingFace Embeddings +4
- •Intelligent Employee Prospecting & Engagement Platform— Full Stack DeveloperPython · LLaMA 3.2 · FastAPI · Flask +2
- •CSMS — Crime Scene Management System— Full Stack DeveloperReact · Node.js · Express.js · SQLite +1
At a Glance
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Typically responds within 4 business hours.
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Divya
Full Stack Developer