Freelancer profile translated to English.

Description

Senior Data & AI Engineer | GCP | MLOps | Generative AI

With over 6 years of experience, I help companies design, migrate, and industrialize data and AI solutions on Google Cloud Platform (GCP).

I work on projects with high technical and business stakes, including:

Migration and modernization of data architectures to GCP
Design of robust and scalable data pipelines (ETL, orchestration, CI/CD)
Deployment of AI & Generative AI solutions (RAG, agents, chatbots, voice bots, automation)
Production deployment and monitoring (MLOps, DataOps)
Implementation of CI/CD pipelines and automation of deployments using Gitlab CI/CD

I have worked on complex projects in demanding environments (Leroy Merlin, Renault, Orange, RATP, Carrefour, L'Oréal, System U), with a strong culture of quality, performance, and production deployment.

👉 Key Expertise:

GCP (BigQuery, Cloud Run, Vertex AI, Dataflow…), Python, SQL, CI/CD, Docker, APIs (FastAPI), RAG, LangChain, LangGraph, GenAI, Agentic AI, Agent AI, LLM, Gitlab.

👉 What I bring:

A pragmatic, results-oriented approach

A strong industrialization capability

Complete autonomy from design to production deployment

Available for migration, build, or optimization missions on GCP.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Asnières-sur-Seine (up to 50km)

Capgemini Adéo Leroy Merlin–
Tech Lead
RETAIL (LARGE RETAILERS)
September 2025 - Today (11 months)
Paris, France
Project: Development of an intelligent voice bot for Leroy Merlin customer service, based on Agentic, internal API, and generative AI.

Development of a generative AI voice bot for Leroy Merlin customer service.
NLU + GenAI for intent detection and automated responses.
Implementation of RAG and integration via backend API (orders, GDPR, identification).
Conversational orchestration and fallback management to a human agent.
Tech Stack: Python, GCP (DataStore, Gemini Enterprise for Customer Experience (Cxagentstudio), Conversation Agents, GCS), Github, API (FastAPI), Agentic
Python Generative AI Gemini Enterprise Cloud GCP Agentic AI
Capgemini Renault
Data Engineer / Generative AI Engineer
AUTOMOBILE
March 2025 - August 2025 (5 months)
Boulogne-Billancourt, France
Project: Agent API / Improve and automate the API lifecycle via Generative AI
Definition of the architecture and working with the solutions architect: design and implement the scenario.
Implementation and industrialization of a RAG preparation agent: Design and deployment of a data pipeline to extract APIs from the Service Registry and transform them via GenAI and LangGraph.
Deployment on Cloud Run, orchestrated by Cloud Scheduler with support for full and delta loading modes (daily update of modified APIs only)
Industrialization of an API generation agent: Development of a FastAPI API deployed on Cloud Run and orchestrated with LangGraph, allowing the generation of OpenAPI/Swagger files from invocations to the internal GenAI platform (Next Gen AI)
Collaboration with DevOps teams for the implementation of CI/CD pipelines and automation of deployments in the production environment.
Tech Stack: Python, GCP (Cloud Run, Cloud Storage, Cloud Scheduler, Vertex), FastAPI, LangGraph, Docker, Gitlab, GitlabCI/CD
Python Google Cloud Platform (GCP) AI Agent Fast API DevOps
Capgemini RATP
Machine Learning Engineer / MLOps
TRANSPORTATION
July 2024 - December 2024 (5 months)
Gare de Lyon, Paris, France
Project: SEM’ALAIN chatbot application, based on generative AI and a RAG architecture, helps support agents in performing their job-related tasks for various subjects within their mission.
Load testing for scaling from 500 agents to 5000 agents
Deployment of the chatbot to 5000 agents. Opening to a wide panel of agents
Scoping, development, and industrialization of a monitoring dashboard on Datadog, and implementation of metrics to monitor the chatbot's performance evaluation.
Perform the RUN process (bug fixing and feeding a backlog of functional enhancements), VSR (regular service verification), and TMA (Third-Party Application Maintenance) preparation.
Tech Stack: Python, Langchain, FastAPI, AWS, Azure, RAG, OpenAI, GPT o-mini, Docker, shell, Gitlab, Datadog (APM, DDTrace, LLMObservability, Auto-instrumenter), Locust, RAGAS, Monitoring/Logs, Openlens, Langfuse.
Python Fast API Langchain Datadog locust