// impact
Over six years I've shipped production systems across organisations large and small — from a global IT consultancy to a focused product team — and the work sits at both ends of the spectrum: AI-native platforms and the plain, hard backend engineering that makes any product run.
years shipping in production
big groups, ESNs & startups
domains — quick to adapt
equally fluent in both
AI-native systems
GenAI · graphs · ML · vision- ▹ GenAI due-diligence platform (KYC / AML / ESG)
- ▹ Document-forensics anti-fraud pipeline
- ▹ GraphRAG + ontology-grounded retrieval
- ▹ Agentic workflows via MCP & tool orchestration
- ▹ ML anomaly detection & computer vision
Platform & product engineering
backend · cloud · data · UI- ▹ Workplace-management SaaS (React / Spring)
- ▹ Event-driven microservices (DDD / CQRS / Kafka)
- ▹ Bare-metal → cloud-native AWS migration
- ▹ Real-time dashboards & IoT analytics
- ▹ CI/CD, Kubernetes & production observability
hallucination & factual error
RAG precision
GraphRAG batch runtime
entity duplication
// skills
Generative AI & LLM Architecture
Agentic Systems & MCP
Knowledge Graphs & Semantic AI
Vector & Graph Databases
Machine Learning & Deep Learning
Computer Vision
AI Platform Engineering
Kubernetes & Containers
Cloud Architecture
Event-Driven Architecture
Backend Engineering
API Security & Hardening
// experience
AI Solutions Architect — GenAI, Semantic AI & Knowledge Graphs
September 2024 – PresentTALIUM · Strasbourg, Grand Est, France
Led the architecture of two AI platforms at TALIUM: a GenAI due-diligence platform for FinTech combining semantic knowledge systems and trustworthy AI, and an anti-fraud system for a public training-funding body detecting fraudulent applications via document forensics and computer vision.
- ▹ Architected a modular, event-driven AI platform for KYC, AML, ESG and compliance workflows — combining knowledge-augmented generation, agentic retrieval and knowledge graphs.
- ▹ Built an anti-fraud detection system — a document-forensics pipeline (OCR, signature detection on attendance sheets, multi-model computer vision with YOLO/olmOCR), XGBoost & Random Forest ensemble scoring, and an Imitation-Learning loop trained on fraud analysts’ feedback for continuous improvement.
- ▹ Designed the semantic foundation with RDF/OWL/SHACL, ontology alignment and LPG-to-RDF translation — cutting entity duplication by 25% and raising RAG precision by +10% on internal benchmarks.
- ▹ Reduced hallucination and factual-error rate by 50% through ontology-grounded retrieval and reasoning.
- ▹ Implemented agentic workflows with MCP and skills-based tool orchestration for structured QA and enterprise-system interaction.
- ▹ Optimised the GraphRAG and LLM-serving stack, cutting batch runtime by 60%.
- ▹ Hardened security via microVM sandboxing, API hardening and AI-oriented UI/UX design.
Full Stack Engineer
September 2022 – September 2024AREMIS Group · France
Designed and evolved Archibus, a React/Spring workplace-management platform for large enterprise clients.
- ▹ Developed full-stack features with Spring, React and Node.js in a microservices architecture.
- ▹ Contributed to AWS architecture and the migration from bare-metal to cloud-native, with CI/CD automation and secure database operations.
- ▹ Worked on real-time workspace monitoring, computer vision and occupancy analytics via IoT devices.
- ▹ Contributed to ML-based occupancy prediction and intelligent-workflow use cases.
- ▹ Took part in technical design, client workshops, POCs, documentation and UI improvements.
Backend Developer
January 2022 – September 2022Euro Protection Surveillance · Strasbourg, Grand Est, France
Contributed to the design, development, testing and deployment of a scalable event-driven microservices platform with Spring Boot, DDD, CQRS, Docker and Kubernetes.
- ▹ Developed event-driven microservices with Spring Boot applying DDD and CQRS principles.
- ▹ Supported containerisation, orchestration and deployment with Docker, Kubernetes and CI/CD pipelines.
- ▹ Maintained service reliability and production availability via automated testing and observability.
Full Stack & AI Engineer — ML, Computer Vision & Kafka Microservices
February 2020 – January 2022CGI · Strasbourg, Grand Est, France
Contributed to industrial solutions combining ML for IoT anomaly detection, computer vision, Kafka event-driven microservices and Angular UI/UX.
- ▹ Worked on machine learning and computer vision for industrial process monitoring and anomaly detection.
- ▹ Developed Spring Boot microservices and event-driven architectures for real-time workflow orchestration.
- ▹ Applied ML on IoT and streaming data for anomaly detection and predictive monitoring.
- ▹ Built Angular applications and dashboards for real-time visualisation.
// education & more
Education
École Nationale Supérieure d’Électricité et de Mécanique (ENSEM)
2017 – 2020Engineering Degree — Software Engineering & Information Technology
Nancy, France
Université de Montpellier
2020 – 2021University Diploma (DU) — Data Science & Big Data
Montpellier, France
CPGE — Lycée Mohamed V
2015 – 2017Classes Préparatoires aux Grandes Écoles — Mathematics & Physics
Casablanca, Morocco
Certifications
AWS Certified Solutions Architect – Associate
Amazon Web Services
Neo4j Certified Professional
Neo4j
Languages
// contact
Let's build something verifiable.