AI Engineer with 2+ years in Generative AI & Data Engineering
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Passionate AI & Data Engineer and Computer Science graduate specialized in Artificial Intelligence, with hands-on experience in AI-powered automation, data engineering, and intelligent application development. I specialize in Generative AI, Agentic AI Systems, Large Language Models (LLMs), and Data Engineering to build innovative solutions that automate workflows, enhance decision-making, and create measurable business value.
Benha University
Bachelor's degree · Computer science
October 1, 2022 – June 30, 2026
Hamber-hub
AI Engineer
February 1, 2026 – June 30, 2026
Cairo, Cairo Governorate, Egypt
NTI
Machine Learning for Data Analysis Trainee
October 1, 2024 – December 31, 2024
Egypt
ITI
Business Intelligence Developer Trainee
August 1, 2024 – September 30, 2026
Egypt
AI Powered Inventory
June 24, 2026 – Present
An advanced autonomous agent developed as part of the graduation project using LangGraph and Google Gemini to interact with inventory databases. • Generates dynamic SQL queries from natural language inputs. • Retrieves and analyzes structured data from inventory systems.
View ProjectRAG-Chatbot
June 24, 2026 – Present
An Agentic Retrieval-Augmented Generation (Agentic RAG) chatbot built with LangGraph, Google Gemini, and CopilotKit. Upload documents, ask questions in natural language, and receive context-aware answers grounded in your uploaded data. • This project implements an agentic RAG system where the agent can decide to retrieve documents, rewrite the question, or respond directly depending on the context. • Provides context-aware answers grounded in user-provided data.
View ProjectTrip Duration Prediction
June 24, 2026 – Present
Built a supervised Machine Learning model to predict NYC taxi trip duration based on spatio-temporal and ride-related features. • Applied multiple Machine Learning algorithms. • Performed data preprocessing, feature engineering, and handling of missing/outlier values. • Evaluated model performance using standard regression metrics (MAE, RMSE).
View ProjectCultural Fit Analysis
The candidate shows a strong interest in AI and data engineering, aligning with the target role of an AI Engineer. The diversity of projects (academic, personal) and internships (AI Engineer, ML Trainee, BI Trainee) indicates a broad learning curve and adaptability. The experience with both academic and industry-relevant tools (LangGraph, Gemini, n8n) suggests a practical and results-oriented mindset. The competitive programming background also points to a drive for continuous improvement and problem-solving, which are positive cultural indicators.
Soft Skills & Operational Fit
The candidate's project descriptions and experience suggest an ability to collaborate in cross-functional teams and a proactive approach to learning new technologies. The focus on automating business processes and improving operational efficiency aligns well with practical application of AI. However, without specific behavioral assessment data, a deeper evaluation of soft skills like leadership, conflict resolution, or advanced communication in a team setting is not possible.