Software Engineer experienced in designing and developing scalable enterprise applications using React.js, Node.js, TypeScript, Python, PostgreSQL, and FastAPI. Strong background in RESTful APIs, backend services, third-party integrations, production applications, and full-stack development. Experienced in building AI-powered applications using LLMs, AI agents, Retrieval-Augmented Generation (RAG), and vector databases.
SOFTWARE ENGINEER
VE3 GLOBAL
- Engineered a Super Agent Platform enabling users to create, configure, and deploy customizable enterprise AI agents, adopted across 3+ client teams.
- Implemented multi-model orchestration and intelligent query routing to dynamically select the most suitable LLM based on query requirements, improving response relevance and optimizing model usage.
- Implemented multi-tenancy across the AI platform, ensuring isolated tenant configurations, data access, and agent workflows for scalable enterprise deployments.
- Spearheaded the end-to-end development and production deployment of an AI-powered document classification platform for NHS Scotland, achieving over 90% classification accuracy and reducing manual review time by 30% through Human-in-the-Loop (HITL) validation.
- Developed scalable Node.js and PostgreSQL backend services for connector integrations, metadata management, and AI workflows, integrating Python-based LLM services and reducing average response latency by 20%.
SOFTWARE ENGINEER INTERN
VE3 GLOBAL
- Built document processing pipelines for cards, documents, and web links, implementing chunking, embeddings, and vector database integration to enable semantic retrieval and context-aware querying across ingested content.
- Integrated Google Drive, SharePoint, and OneDrive for automated document ingestion and processing, implementing secure OAuth 2.0 authentication flows for third-party connectivity and access.
- Developed RESTful APIs and backend services for document metadata management, ingestion workflows, and retrieval operations, improving application responsiveness by 15% and reducing redundant requests by 40%.
UPSC Smart Study Platform
Built a full-stack resource management platform using React.js, Node.js, and Express.js, adopted by 50+ UPSC aspirants to organize and track study materials through Google Drive and OneDrive integrations. Designed RESTful APIs and a PostgreSQL data layer, and implemented a vector database retrieval pipeline using chunking and embeddings, reducing manual material search time by 35% and achieving over 85% Q&A relevance accuracy. Implemented automated email reminders and web-search-based resource discovery, reducing manual resource-hunting time by approximately 30% for active users.
Master of Computer Applications (MCA)
Savitribai Phule Pune University
Bachelor of Science in Computer Science (B.Sc CS)
University of Mumbai
Microsoft Certified: Azure Network Engineer Associate
Microsoft
Oct 2025Microsoft Certified: Fabric Data Engineer Associate
Microsoft
Sept 2026
Attendee · Oct 24, 2026