AI Developer

Ehab is a multidisciplinary AI and automation engineer with a background in engineering and applied AI development. He began his career as a mechanical engineer, later transitioning into the IT field after completing advanced studies at Egypt’s Information Technology Institute (ITI) in Smart Village, specializing in AI and Machine Learning. His core expertise spans intelligent automation, machine learning model integration, and AI-driven process design. Ehab has built end-to-end automation systems from design to production, primarily using UiPath, Power Platform (Power Automate, Power Apps, Power BI), and AWS Lambda. He has also worked on integrating OpenAI, Hugging Face, and document intelligence models into automated workflows—bridging traditional RPA with modern AI-driven automation. Currently, at Tropicquity (UK-based), he continues to deliver AI-driven solutions focused on automation efficiency and workflow optimization. AI/ML Tools: OpenAI, Hugging Face, Document Intelligence, NLP & Computer Vision models Automation Platforms: UiPath, Power Automate, Power Apps, AWS Lambda, Zapier (basic familiarity) Programming Languages: Python, JavaScript, Node.js Visualization & BI Tools: Power BI, Qlik / Kibana dashboards (data visualization and monitoring) AI/Automation Approach: Strong experience in building new automation systems from scratch, not only maintaining existing ones

Bachelor — Mechanical Engineering

Engineering Alexandria University

AI and Automation Engineer | VOIS — Aug 2023 – Present

• Developed automation workflows using UiPath and AWS Lambda.

• Integrated Google Cloud Platform with UiPath to automate document upload to GCP buckets, enhancing workflow efficiency and cloud storage management.

• Built end-to-end RAG models to extract answers from complex documents.

• Worked on prompt engineering using OpenAI and LangChain.

• Created PoCs for AI agents with LangGraph.

• Developed document understanding solutions using Azure AI services.

• Contributed to automation projects using Microsoft Power Apps.

• Collaborated with cross-functional teams to deliver AI solutions aligned with business needs.

• Developed and deployed Azure Cloud Functions to support backend automation tasks and integrate cloud services into enterprise workflows.

AI/Machine Learning Trainee | Information Technology Institute — Oct 2022 – Jul 2023

• Built machine learning projects covering both supervised and unsupervised learning techniques.

• Developed deep learning models for various use cases, including image and text data.

• Processed and visualized datasets using tools like Pandas, NumPy, Matplotlib, and Seaborn.

• Built and fine-tuned NLP models for text classification and generation tasks.

• Worked on computer vision projects involving object detection and image classification.

Mechanical Maintenece Engineer | LAMAR — Feb 2022 – Oct 2022

• Collected comprehensive data sets from TetraPak Machines in processing, filling, and DE sections, including sensor readings and machine stoppage information.

• Utilized traditional tools such as Excel to perform detailed analysis of the collected data, identifying patterns and insights related to package waste and production inefficiencies..

• Collaborated with cross-functional teams to develop data-driven recommendations for process optimization and waste reduction.

• The implementation of these strategies resulted in improved operational efficiency and waste reduction.