Raphael Oualid

Python & AI | LLM · RAG · MLOps · GCP

I help companies design and deploy robust generative AI systems — from RAG architecture to production deployment on cloud infrastructure.

LLM & RAG

Design of end-to-end RAG pipelines on business documentation bases: job offers, HR documents, patient records, educational content. Orchestration of multi-step AI agents with LangGraph. LLM integration (summarization, classification, structured extraction). Stack: LangChain, LangGraph, ChromaDB, HuggingFace, Groq, spaCy.

MLOps & Deployment

Industrialization of ML/AI pipelines in production. Docker containerization, GitLab CI/CD, GCP deployment (Cloud Run, BigQuery). Exposure via FastAPI or Streamlit. Versioning, monitoring, complete documentation.

Data Engineering

Building scalable ETL/ELT pipelines. Web scraping and data extraction (Selenium, Playwright) from LinkedIn, job boards, marketplaces, and directories. Data cleaning, enrichment, and structuring (PDF, API). Normalization, deduplication, quality control.

Sectors

Large accounts, tech startups, HR firms, training organizations, healthcare.

Teaching

Instructor in Master 1 Data/AI (NLP, RAG, LLM architecture) — pedagogical and technical rigor serving each deliverable.

Approach: feasibility audit → tested prototype → documented and maintainable deliverable. GDPR compliant.