Description

Développeur Backend Python / Flask / Django | AI & Data Engineer

Ingénieur logiciel avec 2 ans d'expérience en conception et déploiement de systèmes backend robustes, de pipelines de données complexes et de solutions d'intelligence artificielle en production.

Chez Berexia, j'ai piloté l'architecture d'une plateforme de monitoring transactionnel bancaire traitant +150 000 transactions/jour (Al Barid Bank), et optimisé des workflows ETL avec des gains de performance allant jusqu'à 98% (SCOR SE). J'ai également développé une plateforme microservices de bout en bout pour le World Bank Group, consolidant les données de sécurité alimentaire de 10+ sources avec tableaux de bord cartographiques et 25+ KPIs.

Aujourd'hui, en tant que fondateur de Killy AI, je conçois des agents IA conversationnels (WhatsApp) pour automatiser la prise de rendez-vous et la gestion client, en combinant LLMs, LangChain/LangGraph, n8n et des backends Supabase/PostgreSQL scalables.

Mes domaines d'expertise :

Backend : Python, Flask, Django, FastAPI, NestJS, NodeJS

Data & ETL : pipelines de données, réconciliation, nettoyage et agrégation

IA & RAG : LangChain, LangGraph, MCP, intégration LLMs, agents autonomes

Infrastructure : Docker, Kubernetes, AWS, PostgreSQL, MongoDB, Nginx

Je m'adapte rapidement aux contextes métiers complexes (banque, assurance, institutions internationales) et je livre des solutions fiables, orientées impact mesurable.

Disponible pour des missions freelance en développement backend, ingénierie data ou intégration IA/RAG.

Domaines d’expertise

Langues

Anglais
Bilingue ou natif
Français
Capacité professionnelle complète
Arabe
Bilingue ou natif

Préférences en matière de lieu de travail

En télétravail uniquement

Travaille majoritairement à distance

SCOR SE
Software Engineer
BANQUE & ASSURANCES
juillet 2025 - octobre 2025 (3 mois)
Paris, France
Dramatically enhanced system performance through comprehensive optimization initiatives. Improved file upload performance by 95% by implementing process optimization strategies and backend architectural enhancements. Increased ETL data retrieval efficiency by 98% through strategic query optimization and implementing robust caching mechanisms. Leveraged Python and Flask framework for backend development, integrated MongoDB for NoSQL data management, and utilized Microsoft SQL Server for relational database operations, ensuring scalable and efficient data processing across the application stack.
Python flask Processus ETL (Extract, Transform, Load) Microservices Caching
Travely AI
Software Engineer
juin 2025 - Aujourd'hui (1 an)
Engineered an intelligent iOS SaaS application serving 50+ active users that revolutionizes travel planning through AI-driven cost estimation. Integrated Large Language Models via Gemini API to deliver real-time, intelligent calculations of complex, multi-variable travel expenses including flights, accommodations, activities, and daily costs.
Built a production-grade backend infrastructure deployed on AWS EC2, featuring robust RESTful APIs that handle seamless data processing and communication between the mobile app and AI services. The system manages user requests, processes LLM responses, and delivers accurate cost breakdowns with exceptional performance and reliability.
Designed an intuitive, responsive user interface using SwiftUI, optimized specifically for iOS devices to provide travelers with a clean, modern experience. The app simplifies travel budgeting by eliminating manual research and spreadsheet calculations, empowering users to make informed decisions about their trips instantly.
Technical Stack: SwiftUI (iOS), TypeScript, Node.js, Express.js, AWS (EC2), Gemini API, RESTful APIs
Key Achievement: Successfully launched and scaled to 50+ users with consistent positive feedback on accuracy and user experience.
Node.js Express Gemini OpenAI Typescript
Berexia
Software Engineer
BANQUE & ASSURANCES
juillet 2024 - novembre 2025 (1 an et 4 mois)
Paris, France
• • Led architectural design and deployment of a microservices-based transaction monitoring platform processing 150K+ daily banking transactions across 5+ data sources, making critical technology stack decisions to process and reconcile financial operations.
• • Engineered automated data reconciliation pipelines that identify discrepancies between transaction systems, reducing manual review time and improving data accuracy for internal banking operations.
• • Implemented an API gateway layer with KrakenD to orchestrate communication between authentication, monitoring, and transfer microservices, ensuring secure and scalable data flow.
• • Developed ETL workflows for data cleansing, enrichment, and aggregation of banking transactions from database.
flask Python Microservices Typescript Docker