About parshva
I’m an AI Engineer focused on building end-to-end LLM-powered systems, with hands-on experience designing and implementing retrieval-augmented generation (RAG) pipelines and natural language–to–SQL chatbots. My work centers on improving retrieval quality and system reliability through semantic-aware chunking, vector databases, and metadata-driven search. I’ve built and deployed LLM-based applications in controlled and on-premise environments, enabling secure semantic search over internal document collections and structured data sources. On the system side, I have experience orchestrating multi-stage LLM workflows for tasks such as query understanding, intent modeling, SQL generation, execution, and result summarization. I’ve also implemented intelligent fallback mechanisms to route non-database queries to external knowledge sources when structured data access is not applicable. In addition to AI system development, I have a strong foundation in modern web and backend technologies. I’ve built full-stack and API-driven applications using TypeScript, Node.js, Express, React, and have hands-on experience working with MongoDB and PostgreSQL. This background allows me to design and integrate LLM systems into real-world applications, handling authentication, data persistence, API design, and frontend interaction. I primarily work with Python and have hands-on experience using LangChain, Redis, RabbitMQ, FAISS/ChromaDB, and SQL/NoSQL databases to build backend systems. I’m particularly interested in LLM system design, retrieval evaluation, and bridging the gap between proof-of-concept models and production-ready architectures. I also have a research background, with work published at WWW RelWeb 2025, and I’m actively looking to expand my knowledge.
Key Skills
Experience
Associate
CurrentBeghou
Ai Engineer
Intensity Global Technologies Limited
Designed and implemented an end-to-end RAG-based chatbot deployed in an on-premise environment, enabling secure semantic search over internal documents using Python, LangChain, FAISS/ChromaDB, with Qwen-Instruct for grounded responses and Llama-NeMo Retriever for high-fidelity embeddings. Built a retrieval pipeline leveraging semantic-aware chunking (recursive splitting with structural context) and rich metadata tagging to improve retrieval relevance and support filtered semantic search across document collections. Architected a multi-stage natural language–to–SQL chatbot system, transforming user queries into executable SQL through query classification, intent generation (JSON-based schema), SQL synthesis, execution, and result summarization using chained LLM components. Implemented an intelligent fallback workflow for non-database queries, routing requests to external knowledge sources and returning relevant links, pricing information, and contextual summaries when structured data access was not applicable.
Software Engineer Intern
Velotio Technologies
* Developed and fine-tuned an AI-powered mental-health companion chatbot for prison inmates, along with an admin dashboard featuring detailed inmate insights and real-time socket notifications. * Optimized system performance using Redis caching and Redis keyspace notifications for inactivity-based session management, ensuring faster dashboards and seamless session flows. * Implemented RabbitMQ-based background sentiment analysis and SSE-driven word-by-word response streaming, improving responsiveness and real-time user experience.
Education
The Lnm Institute Of Information Technology
Bachelor Of Technology
Delhi Public School Indirapuram
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Common Questions
What is parshva's expertise?
parshva specializes in RAG Engineer, with expertise in bert, embedding, express, faiss, gcn.
Where is parshva located?
parshva is based in bangalore, karnataka, india.
How much experience does parshva have?
parshva has 1+ years of professional experience.
How can I contact parshva?
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