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Full Stack Engineer with less than a year in AI and Full Stack Development
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Assessing your cultural and operational fit
Highly motivated Full Stack Developer Intern with 1 month of experience in building and deploying RESTful APIs using Node.js, Express, and MongoDB. Proven ability to optimize database queries, implement robust authentication systems (JWT), and develop production-ready UI/UX components. Actively involved in AI/ML projects, including hybrid RAG systems, multi-agent AI for market analysis, and NLP pipelines for recruitment intelligence. Proficient in a wide array of technologies from JavaScript, Python, and TypeScript to FastAPI, PostgreSQL, and various LLMs, ready to contribute to innovative software and AI solutions.
Thapar Institute of Engineering & Technology
B.Tech · Computer Engineering
N/A – June 30, 2027
Indian Institute of Technology (IIT) Patna
Minor · Generative AI & Machine Learning
N/A – June 30, 2026
Warewe Consultancy
Full Stack Developer Intern
June 1, 2025 – July 31, 2025
Gurgaon, Haryana, India
Zidio Development
Full Stack Developer Intern
May 1, 2025 – June 30, 2025
India
DocuQuery - Multi-Tenant SaaS RAG Platform
January 1, 2024 – June 1, 2026
Built production-grade RAG system with 1024-dim Cohere embeddings, pgvector IVFFlat indexing for sub-100ms semantic retrieval; full PDF, DOCX, TXT ingestion pipeline with chunking and overlap. Designed multi-workspace SaaS architecture with Row Level Security (RLS), JWT authentication, and role-based access control (Owner/Admin/Member).
View ProjectHackTrack - AI Hackathon Discovery & Team Formation
January 1, 2024 – June 1, 2026
Implemented semantic teammate search using Sentence-BERT (384-dim embeddings) and cosine similarity; aggregated 500+ hackathons from Devpost, MLH, CList with deduplication and real-time Socket.io chat.
View ProjectHireAI - GenAI-Powered Recruitment Intelligence Platform
January 1, 2024 – June 1, 2026
Built end-to-end NLP pipeline using TF-IDF vectorization and cosine similarity for semantic resume-to-job-description matching; integrated LLM for explainable skill gap analysis and HIRE/CONSIDER/REJECT recommendations.
View ProjectRAG Email Classifier
January 1, 2024 – June 1, 2026
Gmail trigger → vector similarity search (Supabase) → LLM response generation → automated reply + Telegram routing for support tickets.
View ProjectHuman-in-the-Loop CRM
January 1, 2024 – June 1, 2026
AI drafts sales emails → human approval/rejection loop → LLM rewrite on feedback → automated Gmail delivery via Google Sheets + Gemini.
View ProjectMulti-Agent AI Assistant
January 1, 2024 – June 1, 2026
Orchestrated specialized AI agents for email handling, content creation, and productivity via intent-based routing and context sharing.
View ProjectBizIntel AI - Hybrid RAG Business Intelligence System
January 1, 2024 – June 1, 2026
Engineered hybrid RAG pipeline combining FAISS semantic search (40%), BM25 keyword retrieval (30%), and Neo4j graph traversal (30%) with entity-match boost; unified 3 retrieval strategies into a single FastAPI endpoint. Built multi-agent AI system for market analysis and document intelligence with LLM-powered decision support and source attribution.
View ProjectCultural Fit Analysis
The candidate's extensive personal projects, particularly in the GenAI and RAG space, indicate a strong passion for technology and continuous learning, which is a positive cultural fit for innovative and fast-paced environments. The diversity of projects, from business intelligence to recruitment platforms and hackathon tools, shows a broad interest and ability to apply technical skills to various domains. While the experience is primarily academic and personal, the depth of technical engagement suggests a proactive and self-driven individual.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and problem-solving skills through a diverse portfolio of complex personal projects. Their ability to work with cutting-edge AI technologies and integrate multiple systems suggests adaptability and a proactive learning approach. The project descriptions indicate an understanding of full-stack development principles and system architecture, which aligns well with an operational role requiring end-to-end development capabilities.