Freelancer profile translated to English.
Back to original languageAbout Alexandre
👋 From idea to AI product in production — LLMs, Agents, RAG & Claude Code
I'm Alexandre, an AI Engineer with 3+ years of experience on generative AI projects in production: large-scale financial media, SaaS scale-ups, legaltech, consulting.
🤖 LLM Agents & Systems in Production
Design of AI agents (research, deep research, business agents) with Pydantic-AI, Google ADK, LangGraph
LLM content generation pipelines deployed for hundreds of thousands of users
Multi-step orchestration, memory, adaptive mechanisms
📚 RAG & Conversational Systems
Custom RAG systems (LangChain, Qdrant, Chroma, Pinecone)
Business chatbots with authentication, history, continuous evaluation
Advanced prompting (CoT, ToT) and evaluation (RAGAS)
🛠️ Claude Code — Integration & Training
Claude Code workflows for tech teams (hooks, slash commands, sub-agents, MCP, skills)
Tailored training from getting started to advanced uses (agents, automations, CI)
Audit and support for team adoption
⚙️ Productionization & MLOps
FastAPI APIs, AWS (ECS, Lambda, S3, CloudWatch) or GCP deployment
GitHub Actions CI/CD, monitoring, MLflow
Modular architecture, tested code, ready to scale
Stack: Python, Claude Code, LangChain, LangGraph, Pydantic-AI, FastAPI, Qdrant/Chroma/Pinecone, AWS, GCP, Azure OpenAI, OpenAI, Anthropic, Mistral.
Whether it's for an ambitious POC, the industrialization of an LLM system, Claude Code training for your team, or audit/consulting, let's talk.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 15km)
Experience
- The Motley FoolAI EngineerPRIVATE EQUITYJanuary 2025 - Today (1 year and 5 months)The Motley Fool is a leading American investment andfinancial media company, followed by hundreds of thousands of paying subscribersworldwide, producing large-scale stock analysis content.• Designed, developed, and maintained large-scale LLM-based article generation pipelines for 500,000 users, while actively participating in agent PoCs• Contributed as a senior member of a team of 5 AI engineers, with an active role in architectural decisions and best practice definition.• Designed and evaluated several AI agent PoCs using Google ADK and Pydantic-AI (Investment Agent, Research Agent, Deep Research)• Developed pipelines covering +5000 publicly traded stocks.
- Twains aiLLM EngineerMay 2024 - February 2025 (9 months)Remote, Freelance LLM Engineer, Twains aiDevelopment of applications based on LLMs and Generative AI• Design and implementation of advanced conversational systems using RAG (Retrieval-Augmented Generation) architectures• Optimization of costs and response relevance through evaluation and prompt engineering strategies (CoT, ToT)• Implementation of intelligent agents for automated information retrieval and processing• Development of REST APIs with FastAPI for exposing LLM services• Implementation of evaluation and performance monitoring pipelines (RAGAS)• Deployment on AWS (ECS, Lambda, S3, CloudWatch)• Implementation of CI/CD via GitHub Actions to automate testing and deployment Key results: Modular architecture allowing rapid adaptation to different use cases Tech stack: Python, Langchain, Langgraph, Qdrant (vector database), RAG, Chain-of-thought, LLM, AWS, GitHub Actions, FastAPI,
- Juriste du DigitalLLM engineerApril 2024 - April 2024Remote, Freelance LLM engineer, Le Juriste du DigitalCreation of an AI-powered legal audit platform for websites based on generative AI and data• Creation of a Corrective-RAG (Retrieval Augmented Generation)• Implementation of agents, memory, and adaptive mechanisms• Popularization and presentation of key concepts related to the use of LLMs (Large Language Models) Key results: Development of a Chat interface with user history and authentication. Tech stack: Python, Langchain, Chromadb, RAG, Chain-of-thought, Azure OpenAI Service, LLM, Adaptive RAG, Google Cloud Platform,
Reviews
J
Julien
AIKAN
Reviewed on 7/9/2023
Thank you Alexandre for this script that will be very useful to us. Good contact and quality exchanges.
Charles
Data Perspective
Reviewed on 5/26/2022
Thank you for the serious work.
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Education
- Master of Science (STePE)Sciences Sorbonne Université2021
- Expert in Data ScienceData ScienceTech InstituteParcours en alternance sur deux ans permettant de former aux métiers de la data. Statistics, Machine Learning and Deep Learning algorithms -Cloud Computing -Data Wrangling -Software Engineering -Big Data: Hadoop ecosystem and Spark -Two professional certifications (AWS Solutions Architect Associate and SAS Enterprise Miner)
Certifications
- Neural Networks and Deep LearningDeepLearning.AI2022