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AI Engineer with 1+ years in Machine Learning & NLP
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Highly motivated and skilled Machine Learning Engineer with 1.3 years of experience in developing and implementing advanced AI systems, including Retrieval-Augmented Generation (RAG) and Context-Aware Generation (CAG) applications. Proficient in NLP, Computer Vision, and agentic AI, with a strong background in building intelligent chatbots, reporting agents, and OCR systems. Demonstrated expertise in leveraging tools like LangChain, ChromaDB, Neo4j, and Gemini API to deliver innovative solutions.
ACU Egypt
Artificial Intelligent MAJOR · Computer Science and IT
August 1, 2019 – June 30, 2023
Certified IT Consultants CIC
Machine Learning Engineer
February 1, 2025 – Present
India
Nahdet Misr publishing group
AI developer intern
April 1, 2024 – February 1, 2025
India
shadi systems company
AI developer intern
September 1, 2022 – July 1, 2023
India
RAG / Context-Aware Generation Application
February 1, 2025 – June 1, 2026
Built a Retrieval-Augmented Generation (RAG) and Context-Aware Generation (CAG) system using LangChain, ChromaDB, Neo4j, and Gemini API. Developed an end-to-end pipeline including document loading, chunking, embedding generation, semantic retrieval, and LLM-based answer generation. Constructed a Knowledge Graph by extracting entities and relationships from documents and storing them in Neo4j. Enhanced generation with context-aware retrieval by combining vector similarity search (ChromaDB) with graph traversal, enriching retrieved text with structured graph context to improve answer accuracy and reduce hallucinations.
Board Reporting Agent
February 1, 2025 – June 1, 2026
Built an AI-powered reporting agent that interprets natural language queries and generates board-level analytical reports from structured company data. Implemented an intelligent query-to-database mapping mechanism that dynamically identifies the relevant database columns required to answer complex business questions. Developed a data aggregation and analysis pipeline that consolidates information from multiple fields to produce unified datasets suitable for executive reporting and decision support.
Egyptian National ID OCR System
February 1, 2025 – June 1, 2026
Enhanced an existing OCR system for Egyptian National ID cards by extending support to process both the front and back sides of the ID. Implemented expiration date extraction to improve data completeness. Additionally integrated image similarity and visual verification techniques to detect whether an uploaded image corresponds to a valid Egyptian ID, or a non-ID image, improving the reliability of the identity verification pipeline.
Real Estate Assistant (VSO)
February 1, 2025 – June 1, 2026
Developed a multi-path AI agent for a real estate chatbot that dynamically routes user queries to specialized processing pipelines based on intent. Implemented a database retrieval module capable of fetching property information through natural language queries, enabling users to search listings conversationally. Built a Retrieval-Augmented Generation (RAG) pipeline to answer questions using internal company policy documents and integrated an LLM-based conversational module to handle real estate inquiries with refuse an out of scope questions and improve the overall user interaction experience.
Meeting Summarization Agent
February 1, 2025 – June 1, 2026
Developed a Qwen-14B based AI agent designed for meeting summarization and sentiment analysis. The system processes meeting transcripts to generate concise summaries while highlighting the overall discussion sentiment, enabling stakeholders to quickly understand key outcomes and insights without reviewing full conversations.
Arabic Question Generation System
April 1, 2024 – February 1, 2025
Developed an Arabic NLP question generation system using transformer-based models. Prepared Arabic NLP datasets by converting raw paragraphs into sentence-level training data and applying preprocessing techniques. Implemented semantic similarity methods using Word2Word and Word2Vec to identify related words and contextual relationships. Applied Named Entity Recognition (NER) to detect entity types and improve contextual understanding. Finally, fine-tuned an AraBERT model to generate coherent and contextually relevant questions from input sentences.
OCR ON EGYPTION NATIONAL ID
September 1, 2022 – July 1, 2023
Designed and developed an OCR-based system for extracting structured data from the front side of Egyptian National ID cards. Built a computer vision preprocessing pipeline that removes background, applies filtering, and enhances text sharpness, combined with edge detection to isolate the ID card region, improving OCR accuracy. Implemented an OCR module to reliably extract key identity fields such as name, national ID number, and address. The system transforms raw ID images into structured verification data suitable for automated identity processing workflows, ensuring high accuracy and robustness in real-world scenarios.
NLP specialization
coursera
June 1, 2026 – Present
Machine learning specilaization
coursera
June 1, 2026 – Present
Knowledge Graphs for RAG
deeplearning.ai
June 1, 2026 – Present
Machine learning Summer Training
ITI
June 1, 2026 – Present
Deep Learning specialization
coursera
June 1, 2026 – Present
Artificial Intelligent course
science land
June 1, 2026 – Present
computer vision Summer Training
ITI
June 1, 2026 – Present
LangChain Chat with Your Data
deeplearning.ai
June 1, 2026 – Present
Artificial Intelligent Summer Training
ITI
June 1, 2026 – Present
prompt engineering
deeplearning.ai
June 1, 2026 – Present
Building and Evaluating Advanced RAG
deeplearning.ai
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with the target role of an AI Engineer, showcasing diverse applications of AI technologies across NLP, Computer Vision, and Generative AI. The breadth of skills and technologies used (LangChain, Neo4j, various LLMs, OCR, RAG, Agentic AI) indicates a continuous learning mindset and a willingness to explore different domains, which is a positive cultural fit for an innovative AI team. The professional experience, though relatively short, is highly relevant and impactful, suggesting a driven individual. The numerous certifications further underscore a commitment to professional development.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to translate complex business requirements into AI solutions. The diversity of projects suggests adaptability and a proactive approach to learning new technologies. The detailed descriptions imply good communication of technical concepts, which is crucial for team collaboration and stakeholder engagement. The candidate's experience with end-to-end pipeline development suggests an operational mindset, capable of delivering deployable systems.