Experience
Throughout my experience, I’ve worked on projects at the intersection of Artificial Intelligence, Backend Engineering, Distributed Systems, and AI Infrastructure. I’ve designed and developed enterprise multi-agent systems, AI copilots, and distributed AI platforms, architecting scalable backend services, event-driven workflows, and intelligent pipelines powered by LLMs and Retrieval-Augmented Generation (RAG).
Beyond AI development, I focus on building reliable, production-ready software by designing scalable architectures, containerized environments, and observable infrastructure. My goal is to bridge the gap between intelligent algorithms and robust software engineering to deliver AI systems that are secure, maintainable, and built to scale.
AI Platform Engineer
Key Responsibilities:
- - Architected a distributed AI platform using event-driven microservices.
- - Developed a hybrid AI pipeline combining deterministic analysis, semantic retrieval, and LLM reasoning.
- - Built a high-performance Go parser for large-scale source code analysis.
- - Implemented asynchronous backend services with FastAPI and RabbitMQ.
- - Integrated PostgreSQL (pgvector), Redis, and MinIO for AI data processing.
- - Containerized and monitored the platform with Docker, Prometheus, and Grafana.
AI Software Engineer Intern
Key Responsibilities:
- - Designed the global Architecture of the Multi-Agent System , chosing the right tools and technologies to ensure scalability and efficiency.
- - Developped the Multi-Agent System using Python , LangChain , LangGraph and Redis connected to a Vector DataBase and to the CRM (PERN stack) application.
- - Integrated Synchrounous and Asynchronous (with Redis Queue) communication modes
- - Implemented False rooting handling and Agents Tracing with LangSmith.
AI Software Engineer Intern
Key Responsibilities:
- - Developed web scraping scripts to collect real estate data from Mubawab and Avito.ma using BeautifulSoup and Selenium.
- - Implemented a model ingestion workflow: data preprocessing, feature engineering, FAISS Vector Database integration, and model training using LangChain and Ollama.
- - Setting up Docker containers for each component (frontend, backend, ML, DB) to ensure reproducibility and smooth onboarding for other contributors.
Sponsorship and Contact Lead
Key Responsibilities:
- - Managed relationships with technology companies and industry partners.
- - Negotiated sponsorship opportunities for technical events and competitions.
- - Coordinated communication between sponsors, club leadership, and organizing teams.