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AI Engineer with 1+ years in Machine Learning & AI System Design
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Data Scientist and AI Engineer with strong expertise in stochastic modeling, machine learning, and intelligent system design. Project Lead on two end-to-end production systems—a vector search-based recommendation engine (FAISS) and a secure agentic AI framework. Experienced in system architecture definition, security planning, delivery management, and technical team coordination. Currently employed at Wize-Alien, a fast-growing AI startup.
ENIT – École Nationale d'Ingénieurs de Tunis
Master's Degree · Data Science, Actuarial Science & Stochastic Control
August 1, 2021 – June 30, 2023
Faculty of Sciences of Tunis (FST)
Bachelor's Degree · Applied Mathematics
August 1, 2017 – June 30, 2020
Wize-Alien
Junior Data Scientist & AI Engineer
August 1, 2025 – Present
Tunis, Tunis, Tunisia
UIB – Union Internationale de Banques
Data Scientist Intern
April 1, 2023 – September 1, 2023
Tunis, Tunis, Tunisia
AI Recommendation Engine
August 1, 2025 – June 1, 2026
End-to-end semantic recommendation engine combining FAISS vector search, custom embeddings, and multi-stage LLM reranking - with automated multi-format document ingestion (PDF, DOCX, images via OCR). Hybrid scoring fuses vector similarity, business rules, and LLM ranking signals. ML roadmap built on a Learning-to-Rank pipeline (LightGBM LambdaRank) with offline evaluation harness (NDCG, MRR, Precision@K) and LLM-as-judge labelling. Designed 4-phase architecture: document ingestion → custom embeddings → FAISS multi-vector index → cross-encoder reranking + MMR. Built automated OCR pipeline with PyMuPDF and Tesseract (+ Kimi-K2 Vision LLM as salvage layer for degraded docs). Implemented hybrid scoring: CrossEncoder + BM25 + Embedding similarity + Evidence Score + Experience signals. Designed LTR evaluation strategy: synthetic smoke set (CI) + real gold set labelled by LLM-judge + human review. Delivered secured FastAPI REST interface with Docker containerization on Render.
Secure Multi-Agent AI System
August 1, 2025 – June 1, 2026
Production-grade 9-layer microservices architecture orchestrating specialized AI agents via LangGraph StateGraph. Provider-agnostic LLM support (Groq, OpenAI, Anthropic, Ollama) with enterprise security, full observability, and async-first design. Architected LangGraph multi-agent pipeline: orchestrator → security → contextualisation → planning → execution ← validation layers. Built multi-layer security: 131 regex threat patterns (20 categories), Guardrails AI, HMAC inter-agent auth, JWT, Redis rate limiting, circuit breaker. Implemented PII detection (Presidio), pgvector semantic memory, and async DB access via asyncpg + PgBouncer. Set up full observability stack: Prometheus + Grafana dashboards + AlertManager with per-agent cost and latency tracking.
Real-Time Voice Assistant Web Application
August 1, 2025 – June 1, 2026
Developed and deployed a voice assistant application with live in-browser audio interactions. React (Vite) frontend + Python backend, low-latency audio streaming via LiveKit, DB migrations with Alembic, containerized with Docker.
Full Stack JavaScript
CrocoCoder
June 1, 2024 – November 1, 2024
Data-Driven Decisions with Power BI
Coursera
January 1, 2022 – Present
Data Science Orientation
IBM
January 1, 2022 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from recommendation engines to secure multi-agent systems and real-time voice assistants, indicates adaptability and a broad interest in AI applications. Their role as a Project Lead and principal architect aligns well with a senior AI Engineer position, suggesting a proactive and leadership-oriented mindset. The breadth of technical skills across backend, frontend, data, and DevOps further supports a versatile and collaborative team member profile.
Soft Skills & Operational Fit
The candidate demonstrates strong project leadership, system architecture, and team coordination skills. Their experience in designing and implementing security plans, managing delivery quality, and building resilient AI solutions indicates a good operational fit for senior roles. The focus on production-grade systems and compliance suggests a pragmatic and responsible approach to development.