About Me
AI Engineer with hands-on experience across the full agentic AI stack including RAG pipelines and multi-agent orchestration. Delivered measurable impact in an aerospace R&D internship, cutting inference latency by 67% and model size by 70% for real-time deployment.
Skills & Technologies
Work Experience
Development and Validation Intern (AI Department)
Built a Conv1D-LSTM deep learning pipeline for aerospace signal forecasting on 50,000+ datapoints, achieving R2 = 0.986 and reducing phase lag by 85%. Engineered a complete AI/ML workflow ensuring zero data leakage and production-grade reproducibility. Delivered a deployment-optimized Conv1D-GRU variant with 67% lower inference latency and 50% fewer parameters.
Projects
MCP Tool Agent
Developed and deployed a Model Context Protocol (MCP) server in Python using Groq, implementing a multi-turn agentic tool-use loop across 5 LLM-callable tools.
Multi Agent Blog Writer
Engineered a 3-agent CrewAI pipeline that turns a single topic into a publication-ready blog post with SEO metadata, requiring zero manual prompting between steps.
RAG Based Document QA System
Developed a retrieval-augmented generation pipeline that ingests PDFs, chunks, and embeds content into a FAISS vector store, answering natural-language queries with source grounding.