About Me
Results-driven AI Engineer with 1+ year of production experience architecting LLM-powered systems, Agentic AI workflows, and RAG pipelines. Proven delivery: 35% accuracy lift on ML models, 40% latency reduction on live APIs, and 90% manual-effort cut via LLM automation.
Skills & Technologies
Work Experience
AI/ML Engineer Intern
Architected AgroSight RAG knowledge base by ingesting and chunking 50K+ agronomic research papers into Qdrant vector stores. Implemented LangChain retrieval chains, achieving 92% answer relevance on crop advisory queries. Developed FastAPI endpoints for the RAG system, handling 200+ daily farmer queries with sub-300ms response time.
Full-Stack Engineer
Engineered an insurance premium predictor with automated ETL pipelines, achieving a 35% uplift in prediction accuracy. Deployed production-grade Flask REST APIs serving 100+ daily quote requests with sub-200ms latency.
Front-End Developer
Delivered responsive web applications with UX optimizations that improved user retention by 30%. Implemented SEO improvements that drove a 25% increase in organic traffic.
Projects
RAG — AI Crop Intelligence Platform
Designed an Agentic AI system for real-time crop disease detection and personalized advisory. Constructed an end-to-end RAG pipeline achieving 92% answer relevance.
Stock Trend Predictor
Developed a multi-layer LSTM forecasting model with live retraining and sliding-window updates.
Fake SMS & Link Detector
Built an NLP phishing-detection classifier achieving 92% precision on SMS and malicious-link identification.
Insurance Aggregator Platform
Developed a full-stack insurance comparison platform aggregating real-time quotes from 10+ provider APIs.
Blog Automation Agent
Built an automated workflow to generate SEO-ready blog articles using LLMs.
Education
Master of Computer Applications
Computer Applications
Bachelor of Science (Hons)
Agricultural Science