AI Engineer with 2 years of hands-on experience building Large Language Model (LLM) applications, conversational AI solutions, Retrieval-Augmented Generation (RAG) systems, and intelligent automation platforms. Experienced with Python, LangChain, Hugging Face, FAISS, Streamlit, FastAPI, and Azure AI services. Skilled in developing scalable AI solutions, optimizing prompts, integrating vector databases, and delivering production-ready AI applications.
Expertise & skills
Selected projects
AI Contract Review Assistant
Built an LLM solution that summarizes legal documents and answers contextual questions.
- Developed document ingestion pipelines.
- Implemented RAG using FAISS.
- Integrated OpenAI APIs.
- Created FastAPI endpoints.
- Optimized prompts for accuracy.
- Performed testing and debugging.
Internal IT Helpdesk Copilot
Developed an AI assistant for resolving employee IT queries.
- Designed conversational workflows.
- Integrated company knowledge base.
- Implemented chat history.
- Built Streamlit interface.
- Improved response quality using prompt engineering.
Meeting Notes Generator
Created an AI application that converts meeting transcripts into structured summaries and action items.
- Processed transcript files.
- Generated summaries using LLMs.
- Developed export functionality.
- Built REST APIs.
- Validated generated outputs.
Knowledge Search Portal
Developed semantic enterprise search for technical documentation.
- Indexed documents.
- Generated embeddings.
- Implemented semantic retrieval.
- Integrated Azure OpenAI.
- Enhanced retrieval accuracy.
Ways of working
Certifications
- Microsoft Certified: Azure AI Fundamentals (AI-900)
- Microsoft Certified: Azure Fundamentals (AZ-900)
- Hugging Face NLP Course
- Generative AI Fundamentals
Education
- 2024
Master of Technology (M.Tech.) – Artificial Intelligence
Gujarat Technological University (GTU)
- 2022
Bachelor of Engineering (B.E.) – Computer Engineering
Gujarat Technological University (GTU)
Achievements
- Built multiple production-ready LLM applications.
- Improved document search with semantic retrieval.
- Developed scalable AI APIs.
- Enhanced response quality through prompt optimization.
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