Data & AI Engineer from Morocco specializing in machine learning, deep learning, computer vision, NLP, agentic AI systems, and real-time data pipelines. Two production deployments: MeetFlow (multi-agent SaaS cutting automotive documentation time by ~70%) and AgriScan (crop disease AI classifier with 94%+ accuracy).
Data & AI Engineer
abdelazizlairgi@gmail.com
+212701146944
Morocco
Computer vision systems, NLP pipelines, deep learning model development and production deployment. Experience with TensorFlow, PyTorch, YOLO, OpenCV, Hugging Face, and scikit-learn. Capable of building end-to-end ML systems from data preprocessing to production serving.
Real-time streaming data pipelines using Apache Kafka, Apache Spark, and Hadoop. ETL pipeline design, data warehouse architecture, and BI dashboard development with Power BI and SQL Server. Experience integrating large-scale data workflows on cloud and on-premise infrastructure.
Design and development of autonomous multi-agent platforms using LangChain, LangGraph, and frontier LLMs (Claude, GPT-4, Gemini). Built production agentic systems including a Microsoft Teams meeting intelligence SaaS with real-time audio transcription via Deepgram and structured meeting reports.
Decentralized application development using Hyperledger Fabric. Smart contract implementation for supply chain traceability and multi-party authentication systems.
Python, TensorFlow, PyTorch, Keras, scikit-learn, YOLO, OpenCV, Hugging Face, LangChain, LangGraph, FastAPI, React, Next.js, JavaScript, TypeScript, Apache Kafka, Apache Spark, Hadoop, Hive, Airflow, PostgreSQL, MySQL, SQL Server, MongoDB, Redis, Docker, Git, Linux, Power BI, Tableau, Metabase, Hyperledger Fabric, Deepgram, Whisper, Claude API, OpenAI API, Gemini API
Abdelaziz Lairgi, known as Aziz, is a Data & AI Engineer based in Morocco. He specializes in building production-grade AI systems, real-time data pipelines, and autonomous multi-agent platforms. With hands-on experience at Capgemini Engineering, XAI SARL, and HSE University, Aziz bridges the gap between research-grade AI and production-ready deployments.
Aziz is currently seeking roles in AI Engineering, Data Engineering, or Applied Generative AI. He is available for remote work and collaborations worldwide.
abdelazizlairgi@gmail.com |+212701146944 | Available for remote projects worldwide
AI & Data Engineer with two production deployments — MeetFlow, a live multi-agent SaaS platform that cut automotive documentation time by ~70%, and AgriScan, a crop AI classifier with 94%+ accuracy across 9+ plant species.
I build across the full AI stack: LLMs & agentic AI (LangChain, LangGraph, RAG), real-time data pipelines (Kafka, Spark), deep learning (TensorFlow, PyTorch), and cloud deployment (Docker, Oracle Cloud).
Previously at Capgemini Engineering, XAI SARL, and HSE University. Seeking roles in AI Engineering, Data Engineering, or Applied Generative AI.
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About Me
I'm Aziz Lairgi, an AI & Data Engineer based in Casablanca, Morocco — I build AI systems that actually ship to production and generate measurable impact. My work sits at the crossroads of agentic AI, large-scale data engineering, and deep learning.
At Capgemini Engineering, I architected MeetFlow — a fully autonomous multi-agent SaaS platform for Microsoft Teams that eliminated manual meeting documentation for an automotive supply chain, cutting documentation time by ~70% and achieving >95% bot join reliability across French, English, and Arabic meetings. At XAI SARL, I deployed AgriScan, a crop disease classifier reaching 94%+ accuracy across 9+ plant species — currently live in production.
I operate at the cutting edge of the AI stack: LLM orchestration with LangChain, LangGraph & MCP, RAG pipelines and vector databases, real-time data engineering (Kafka, Spark, Hadoop), computer vision and NLP, and cloud-native deployment on Oracle Cloud and Azure. I benchmark frontier models — Claude Opus 4, DeepSeek R1, Qwen3 — and choose the right tool for the job, not the trending one.
Beyond engineering, I'm driven by creative technology — from game development with Unity 3D to music production with FL Studio. I believe the best engineers combine rigorous technical thinking with a creative mindset that sees what could be, not just what already exists.
Tech I Work With
Creative Tools
Experience
AI Engineering Intern (PFE) — Capgemini Engineering
Jan–Jun 2026 · 6 months
AI & Computer Vision Intern — XAI SARL
2025 · 2 months
Research Intern (Fault Analysis) — HSE University
2025 · 2 months
Data Science Intern — Innolia Consulting
2024 · 1 month
Selected Work — 10 projects · 2024—2026
Production AI systems, agentic platforms & data pipelines — the same 10 case studies you’ll find in the archive.
View archive — 10 projectsModern enterprise meetings suffer from fragmented documentation, missed action items, and unstructured follow-ups. MeetFlow was built as a fully autonomous mult…
View case studyAgricultural yields are heavily impacted by delayed disease diagnosis in crops. AgriScan addresses this by providing farmers with an accessible, real-time diagn…
View case studyTraditional CRMs are powerful but often suffer from low adoption due to complex interfaces. This project reimagines pipeline management by embedding a fully cap…
View case studyManaging a massive logistics fleet requires sub-second visibility into vehicle health and location. I architected and deployed an end-to-end Data streaming pipe…
View case study04 featured — 10 total in archive · AI + Data + BI
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