AI Software Engineer | 1.5+ Years of Exp | RAG, LLMs, GenAI, Vector Databases, Agentic AI

I am an AI Software Engineer specializing in architecting and deploying production-grade Generative AI systems, Retrieval-Augmented Generation (RAG) pipelines, and intelligent agentic workflows. With a strong foundation in Information Technology and Information Systems, my expertise lies at the intersection of system design, semantic search optimization, and enterprise-scale workflow orchestration. My technical approach prioritizes operational efficiency, data security, and high-precision retrieval. I have a proven track record of building secure, self-hosted, air-gapped AI solutions for sensitive government and enterprise use cases, ensuring zero third-party data exposure while making complex data landscapes seamlessly accessible.

Core Areas of Expertise

• Generative AI & Agentic Workflows: Designing multi-turn reasoning agents, stateful memory systems, and automated LLM workflows using frameworks like LangChain, LangGraph, and Claude.
• Advanced RAG Architecture: Implementing production-level retrieval pipelines utilizing hybrid search (BGE-M3 dense + BM25 sparse parsing), cross-encoder re-ranking, and advanced document-aware chunking.
• Enterprise Integration: Building semantic-to-SQL pipelines, secure internal prompt engineering studios, and automated analytical layers over legacy relational databases.
• Backend & Infrastructure: Developing high-performance APIs and microservices using Python, FastAPI, Node.js, and NestJS, combined with robust containerization and orchestration via Docker.

Key Technical Achievements

• Government-Grade RAG Systems: Built a fully self-hosted, on-premise RAG pipeline for the Government of India’s PPP infrastructure division. Successfully ingested over 1,200 highly sensitive documents using Docling, Surya OCR, Qdrant, and Ollama, implementing custom metadata tagging and atomic chunking strategies.
• Conversational Inventory Intelligence: Engineered a semantic-to-SQL pipeline and conversational AI layer over multi-warehouse systems, enabling non-technical users to query database infrastructure securely using plain English.
• Internal Tooling Orchestration: Developed proprietary internal prompt engineering tools supporting role-based workflow orchestration, allowing rapid iteration on LLM interactions without codebase modifications.

Technical Toolkit

• Languages: Python, JavaScript, Java, SQL
• AI & Frameworks: LangChain, LangGraph, RAG Pipelines, Hybrid Search (BGE-M3 + BM25), Ollama, Docling, FastAPI, NestJS, Node.js, React
• Databases & Tools: Qdrant, Vector Databases, PostgreSQL, MySQL, Redis, Docker, Git, Linux
• Methodologies: System Design, Semantic Search, Agentic Workflows, REST API Development

Education & Credentials

• MBA in Information Systems & Business – Mumbai University (2026)
• Bachelor of Engineering in Information Technology – Mumbai University (CGPA: 8.96/10)
• Diploma in Computer Engineering – Government Polytechnic Ratnagiri
• Certifications: AWS Cloud Practitioner Essentials, Docker Mastery, API Security