Nicolas VIOLOT

- Designed agentic AI apps using LangChain and LangGraph to enable LLMs to understand and generate Hexaly Modeler code via advanced prompt engineering and fine-tuning - Integrated RAG pipelines to support user learning in the Hexaly ecosystem - Built translation tools between natural language, Hexaly Modeler, and the Python SDK - Responsible for the integration of generative AI tools into core products - Created an MCP server to manage interactions between LLM agents and Hexaly services

- Led development of an AI assistant that interprets images, diagrams, and text to generate data workflow Python scripts using LangChain and prompt engineering - Built a full-stack Flask app enabling users to create custom web crawlers for CV bank sites using AI, with API integration and responsive UI using HTML/CSS/JS - Contributed in Agile/SCRUM teams, supporting sprint planning, iterative dev, and cross-functional collaboration

- GPA: 3.67/4.00 - Relevant Courses: Object-Oriented Analysis & Design in UML, Advanced Web Programming, Java Programming, Computer Architecture, Networks & Protocols

- GPA: 3.75/4.00 - Winner of the Hackathon: Data Analysis & Prediction for Paris Transport, sponsored by Microsoft & Capgemini. - Relevant Courses: Chatbots & Generative AI – Machine Learning – ML in Production – NLP – Reinforcement Learning – Neural Networks & Deep Learning – Mathematics for Data Science – Cloud Computing – Advanced Databases – Big Data Ecosystem – Data Management & Ethics