About Me
I'm an AI Engineer at Edulga, where I architect production-grade agentic AI systems and autonomous agents for enterprise knowledge management. My expertise spans agentic workflows with multi-step reasoning, RAG architectures (GraphRAG, Neo4j, VectorDB), and LLM optimization—with a proven track record of delivering measurable business impact: 85% performance improvements and 50% cost reductions in production environments.
I specialize in building intelligent systems that autonomously reason, use tools, and self-correct. My technical foundation combines agentic AI frameworks (LangGraph, autonomous agents), knowledge graph engineering (Neo4j, vector search), computer vision (medical imaging with 93% recall, explainable AI), NLP, and production ML deployment (FastAPI, Docker). My journey includes securing first place in two university research competitions and progressing from R&D roles to deploying production AI systems serving real users at scale.
When I'm not coding or studying, you'll find me playing tennis 🎾, biking 🚲, or enjoying a game of football ⚽.
Education
B.Sc. in Electronics and Computer Engineering
Nile University
2019 - 2024
- • Cumulative Grade: Very Good
- • Presented 6 posters in the Undergraduate Research Forum (UGRF), winning first place in two.
- • Full Year Research Graduation Project Grade: Excellent - A
Experience
Edulga
Full-Time
AI Engineer
August 2025 – Present
- • Architected and deployed production platform with GraphRAG pipeline, Neo4j knowledge graphs, and Pinecone vector search and LangChain orchestration for enterprise knowledge management at scale
- • Engineered distributed ML systems achieving 85% performance improvement through parallel processing, HTTP/2 connection pooling, and intelligent caching strategies
- • Optimized multi-tenant microservices architecture with FastAPI, and Docker, reducing infrastructure costs by 50% while maintaining sub-second query latency
- • Implemented production-grade AI workflows with comprehensive testing (97+ tests), monitoring, and cost tracking for LLM API optimization
Al-Farid Scan
Part-Time
R&D Machine Learning Engineer
March 2024 – March 2025
• Improved MRI classification algorithms by 20%, enhancing diagnostic accuracy through innovative machine learning techniques.
The Central Administration for Water Resources and Irrigation
Internship
Data Analyst
Dec 2023 – Jan 2024
- • Database management (querying, searching, etc.).
- • Assessing the performance of telemetry systems and developing solutions for improvement.
Technical Expertise
AI & Machine Learning
- Large Language Models (LLMs) - Fine-tuning, Prompt Engineering, LLM Optimization
- RAG Systems - Retrieval Augmented Generation, GraphRAG Architectures
- AI Systems & Agentic AI - LangChain, LangGraph, Multi-Agent Workflows
- Natural Language Processing (NLP) - BERT, Transformers, Sentence Embeddings, Arabic NLP
- Computer Vision - Medical Imaging, Grad-CAM, Explainable AI (XAI)
- Vector Databases - FAISS, Pinecone, Weaviate
- Knowledge Graphs - Neo4j, Graph Neural Networks
Frameworks & Tools
- ML Frameworks - PyTorch, TensorFlow, Scikit-learn, Hugging Face
- LLM Orchestration - LangChain, LangGraph, Sentence Transformers
- MLOps & Deployment - MLflow, Docker, Kubernetes, FastAPI
- Cloud Platforms - AWS, Azure, Google Cloud
- Databases - SQL, NoSQL, Vector DBs
- Version Control & CI/CD - Git, GitHub Actions, GitLab CI
- Data Processing - Pandas, NumPy, OpenCV
Completed Courses
Machine Learning Specialization
Coursera - DeepLearning.AI
Deep Learning Specialization
Coursera - DeepLearning.AI
PyTorch: Deep Learning and Artificial Intelligence
DeepLearningCourses.com
OpenCV Course – Full Tutorial with Python
FreeCodeCamp
Achievements
Band Score 7 - C1
IELTS Academic Exam
Campus Director - 37 teams
Hult Prize at NU
Finalist - Shortlisted Participant
European Union EBTIKAR Competition
First Place - Two times
Undergraduate Research Forum (UGRF)
Finalist - Shortlisted Participant
UNDP AfriClimate Inclusive Innovation Bootcamp
Presented 6 Research Posters
Undergraduate Research Forum (UGRF)