AI Engineer with 1+ years in Generative AI & LLM Applications
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AI Engineer with hands-on experience in Generative AI, LLM applications, Retrieval-Augmented Generation (RAG), and AI-powered automation systems. Skilled in building intelligent applications using LangChain, vector databases, Flask, and transformer-based models. Passionate about Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and building intelligent applications that solve real-world business problems.
Modern Education Society's College of Engineering
Bachelor of Engineering
N/A – June 30, 2025
The Strelema
AI Intern
November 1, 2025 – January 31, 2026
Pune, Maharashtra, India
AI Adventure
Data Analyst Trainee
January 1, 2025 – October 31, 2025
Pune, Maharashtra, India
Lets Grow More
Data Analyst Intern
March 1, 2023 – April 30, 2023
Pune, Maharashtra, India
AI Medical Chatbot
June 25, 2026 – Present
Built an end-to-end Generative AI medical chatbot using LangChain, Gemini LLMs, RAG architecture, and NLP techniques with a 637-page custom medical knowledge base. Developed a scalable retrieval pipeline using PDF processing, recursive text chunking, embeddings, semantic search, and Pinecone vector database. Implemented context-aware conversational AI using Hugging Face Sentence Transformers and vector similarity search. Built REST APIs and backend services using Flask for real-time conversational interactions. Designed modular AI workflows enabling intelligent document understanding and medical query answering.
LinkSage – AI-Powered Web Knowledge Extractor
June 25, 2026 – Present
Developed an LLM-powered web knowledge extraction platform using Streamlit, LangChain, and NLP pipelines. Implemented semantic search and intelligent retrieval using FAISS vector database and transformer embeddings. Built contextual Q&A workflows for extracting insights from multiple web sources.
Financial Risk Assessment for Loan Approval
June 25, 2026 – Present
Built a loan approval prediction model using Linear Regression and Python. Performed data cleaning, preprocessing, and feature engineering to prepare the dataset. Conducted exploratory data analysis (EDA) to identify key factors influencing loan approval. Evaluated model performance using appropriate regression metrics and visualizations. Generated insights to support data-driven loan approval decisions.
Cultural Fit Analysis
The candidate's project diversity, ranging from medical chatbots to web knowledge extractors and financial risk assessment, indicates a broad interest in applying AI across different domains. Their experience as an AI Intern and Data Analyst Trainee aligns well with an AI Engineer role, showing a progression towards more specialized AI tasks. The breadth of skills listed, including various AI/ML frameworks and data tools, suggests adaptability and a willingness to explore different technologies, which is a good fit for dynamic tech environments.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach through personal projects, indicating self-motivation and a drive to learn and apply new technologies. Their internship experiences show an ability to work in structured environments and contribute to team goals, particularly in data analysis and AI development. The project descriptions are clear, suggesting good communication of technical work.