Open to opportunities

Mostafa Mohamed

@mostafamohamed8

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AI Engineer building LLM agents and RAG pipelines for production-ready, healthcare-ready AI.

Egypt

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What I'm looking for

I’m looking for a role where I can build production-ready LLM apps—RAG pipelines, AI agents, and NLP solutions—especially in healthcare. I want a team that values end-to-end ML workflows, strong engineering practices, and continuous improvement.

I’m an AI Engineer focused on LLM-based systems, Generative AI, Machine Learning, and Deep Learning. I design and deploy AI agents, RAG pipelines, NLP solutions, and end-to-end ML workflows that translate complex business needs into scalable, production-ready outcomes.

In my internship at YOUXEL Technology, I built and deployed LLM-based multi-agent systems with Flowise, embeddings, vector stores, and fine-tuning approaches. I also designed and optimized RAG (Retrieval-Augmented Generation) pipelines to improve accuracy and response quality, along with prompt engineering to reduce manual intervention.

Through my Data Science & AI Training Program + Intern at Epsilon, I worked end-to-end on medical datasets—preprocessing, EDA, and building supervised/unsupervised models using Python and Scikit-learn. I developed and deployed lightweight ML web applications (including a diabetes prediction system) for real-time inference.

I bring research momentum from my M.Sc. in Computing at Queen’s University (AI/ML/NLP focus) and an applied mindset from selected participation in Egypt’s Digilians initiative with MCIT, Google, Microsoft, and Dell. I’m especially drawn to building AI for healthcare, where reliable document understanding and AI-assisted decision support matter.

Experience

Work history, roles, and key accomplishments

AI Engineer Intern

YOUXEL Technology

Jul 2025 - Aug 2025 (1 month)

Built and deployed LLM-based multi-agent systems using Flowise, including embeddings/vector stores and fine-tuning techniques. Designed and optimized RAG pipelines and applied prompt engineering for improved LLM outputs, along with NLP-driven document processing and internal automation.

Flowise Embeddings Vector Stores Fine Tuning Prompt Engineering Natural Language Processing (NLP)Document Processing AI Automation

Data Science & AI Intern

Epsilon

Feb 2022 - Feb 2024 (2 years)

Implemented supervised and unsupervised machine learning models covering classification, regression, and clustering as part of a training program and internship. Performed data preprocessing and EDA on medical datasets and deployed a diabetes prediction system as a lightweight Flask web application for real-time inference.

Supervised Learning Unsupervised Learning Classification regression Clustering Python scikit learn data preprocessing Flask Web Based ML

Education

Degrees, certifications, and relevant coursework

Egyptian Military Academy & MCIT

Program (Digilians), Digital Pioneers Initiative

2025 -

Activities and societies: Selected for a national digital transformation program with MCIT, Google, Microsoft, and Dell.

Selected participant in Egypt's national Digilians – Digital Pioneers Initiative in partnership with MCIT, Google, Microsoft, and Dell.

Queen's University

Master of Science (Computing), Artificial Intelligence, Machine Learning, and NLP

2026 -

Project-based M.Sc. in Computing at Queen's University focusing on AI, machine learning, and natural language processing. Applied AI projects with hands-on collaboration with leading researchers in AI and computing.

Helwan University

Bachelor of Science, Computer Science & Artificial Intelligence

2019 - 2023

Grade: A+

B.Sc. in Computer Science & Artificial Intelligence from Helwan University (GPA 3.52/4.0, Grade A+). Graduation project 'Meditech'—an AI system for reading medical prescriptions using deep learning and OCR (94% accuracy).