AI Engineer with less than a year in Generative AI and LLM-based solutions.
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AI Engineer with hands-on experience building and deploying Generative AI and LLM-based solutions. Worked on RAG-based chatbots and agentic AI workflows for intelligent automation and enterprise use cases. Strong skills in Python, LangChain, transformer models, prompt engineering, embeddings, semantic search, and vector databases. Experienced in building production-ready RAG pipelines and AI agents using LangChain, CrewAI, and LangGraph frameworks.
M.I.T, Aurangabad, INDIA
Master of Engineering · Mechanical
August 1, 2018 – June 30, 2018
A.V.C.O.E, Pune University, INDIA
Bachelor of Engineering · Mechanical
August 1, 2013 – June 30, 2013
Bantosh Agri Fintech Pvt Ltd
AI ENGINEER INTERN
January 1, 2026 – Present
India
Project 2: Enterprise Agentic RAG Customer Support Chatbot
June 24, 2026 – Present
Developed and deployed a live, cloud-hosted Agentic RAG customer support system that allows website users to interact with an AI agent via a floating web widget.
Project 1: Enterprise RAG Chatbot
June 24, 2026 – Present
Built a production-grade RAG chatbot using LangChain to answer queries on sales, financial, and service data sourced from CSV, Excel, PDF, and Word documents. Implemented RecursiveCharacterTextSplitter (512 tokens, overlap), MiniLM embeddings, FAISS vector store, and cosine-similarity top-k retrieval, with prompt-guarded GPT-based LLM generation. Developed backend APIs in Python/FastAPI and a Streamlit frontend, ensuring reliable, context-grounded, enterprise-ready responses.
Retail Automated Algorithmic Trading Architecture ("Algoboat")
June 24, 2026 – Present
Deployed a containerized, asynchronous algorithmic trading system on Render using Python, FastAPI, and Uvicorn, integrated with Angel One SmartAPI for live market data, indicator computation, and automated trade execution. Built a secure private Telegram bot interface for real-time command control, monitoring, and logging of trading operations.
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the 'AI Engineer' target role, focusing on practical applications of Generative AI, RAG, and agentic systems. The diversity of projects, from enterprise chatbots to algorithmic trading, shows a broad interest in applying AI solutions across different domains. The use of various tools and frameworks (LangChain, CrewAI, FastAPI, Streamlit, Docker, Azure, AWS) indicates adaptability and a willingness to learn and integrate new technologies. The personal project 'Algoboat' highlights initiative and a passion for AI outside of formal work, which is a positive indicator for cultural fit in an innovative AI team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a collaborative approach, especially in the intern role where they 'collaborated closely with the lead engineer and team'. The focus on 'testing, logging, and edge case handling for production readiness' suggests an attention to operational details and reliability. The development of a secure Telegram bot for monitoring trading operations also points to a proactive approach to system management.