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AI Engineer with 1+ years in LLM Systems & AI Pipelines
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AI Systems Engineer with hands-on experience in building production-grade LLM systems, retrieval-augmented applications, and scalable AI pipelines. Experienced in designing backend-integrated AI solutions including fine-tuning, inference optimization, and graph-based recommendation systems.
Cairo University
Bachelor's Degree · Computer Science and Artificial Intelligence
August 1, 2022 – June 30, 2026
Datalentech
AI Developer Intern
March 1, 2026 – April 1, 2026
Cairo, Cairo Governorate, Egypt
MasteryHub ITS
Artificial Intelligence Engineer
January 1, 2026 – Present
Cairo, Cairo Governorate, Egypt
MasteryHub ITS
Artificial Intelligence Intern
August 1, 2025 – December 1, 2025
Cairo, Cairo Governorate, Egypt
National Telecommunication Institute (NTI)
Computer Vision Intern – AI Summer Internship Program
July 1, 2025 – August 1, 2025
Cairo, Cairo Governorate, Egypt
NTI - Huawei Egyptian Talents Academy
AI Trainee
April 1, 2025 – July 1, 2025
Cairo, Cairo Governorate, Egypt
Graph-Based Learning Recommendation System
March 1, 2026 – April 1, 2026
• Built a graph-based learning path system using DFS and topological sorting to generate structured skill sequences based on prerequisite relationships • Designed an embedding-based ranking engine combining cosine similarity, skill weights, and content quality scoring for personalized recommendations • Implemented a dynamic content pipeline with external fetching, database expansion, and filtering to maintain up-to-date learning resources
View ProjectLLM-based Agentic RAG System for Automated Presentation Generation
March 1, 2026 – Present
• Built an AI presentation agent that generates structured slide content and narration using LLM-based multimodal pipelines • Designed and implemented an agentic RAG system using LangChain, integrating retrieval, tool usage, and session-aware memory for real-time content generation • Developed a Text-to-Speech service using Gemini TTS, supporting single and multi-speaker voice synthesis for dynamic presentation delivery
SpeakOut AI Content Moderation System
December 1, 2025 – Present
• Built and fine-tuned LLMs using SFTTrainer with LoRA-based adaptation, through 4-bit quantization and mixed precision (FP16/BF16) • Developed a lightweight local-first moderation model optimized for low-latency inference, integrated with the frontend for real-time user feedback using ONNX (INT8 quantization) • Engineered GPU lifecycle management and cron-based scheduling system with queue-driven activation logic to optimize resource utilization and reduce idle compute time • Implemented high-throughput batch processing pipeline handling up to 100 posts per batch with optimized inference efficiency (~0.13-0.15s per post)
View ProjectAI Agent for Diabetes Diagnosis
September 1, 2025 – Present
• Fine-tuned LLAMA and BioGPT on a custom medical dataset, deployed via FastAPI and Gradio
View ProjectCultural Fit Analysis
The candidate's project portfolio is diverse, covering LLM moderation, recommendation systems, agentic RAG, and medical AI, which aligns well with the varied demands of an AI Engineer role. The experience with multiple internships and a current full-time role at MasteryHub ITS, alongside personal projects, indicates a strong drive and commitment to the field. The breadth of skills listed (Python, C++, TypeScript, FastAPI, AWS, Vector Databases) suggests a willingness to explore and integrate different technologies, which is beneficial for cultural fit in a dynamic AI environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving approach, particularly in optimizing resource utilization and inference efficiency. The diversity of projects suggests adaptability and a strong learning curve. However, without direct assessment data on communication or teamwork, these are inferred from the quality of project descriptions.