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Alhaitham Gamal M.

@haitham1996

monthly-level-four.svg
5.0
4

2.8

2.8

100%

Software Developer

$30 USD / Hour

・

Flag of

Egypt (4:19 AM)

・

Joined on September 27, 2018

・

1 Recommendation

$30 USD / Hour

・

? AI Prompt Engineer & Full-Stack Developer | Python • Django • Java • Low Code • Blockchain Hi! I'm Alhaitham — a results-driven developer and certified Prompt Engineer with over 3 years of experience building scalable web apps, automation bots, and smart AI workflows. I’ve worked at top-tier companies like ATOS, Vodafone, and Qeema, delivering real-world solutions using: Python, Django, Java (Spring, Hibernate, JEE) REST APIs, Web Scraping & Automation Bots Low-Code Platforms (OutSystems with React) Blockchain Smart Contracts (Solidity / Web3) ? But I don't just build systems — I also build intelligence into them. I'm also a skilled Prompt Engineer, crafting optimized ChatGPT / AI prompts for: Marketing & content creation Business process automation AI-powered apps, chatbots, and SaaS tools SEO blogs, emails, and full eBooks Midjourney / DALL·E art generation Whether you're a startup, agency, or enterprise — I help bring your ideas to life faster and smarter, combining clean code with prompt-powered intelligence. ⚡️ I'm a fast learner, deeply passionate about tech, and always eager to bring creative solutions that just work. Let’s build something amazing — together.

Verifications

On time

95%

On budget

95%

Accept rate

75%

Repeat hire rate

100%

Freelancer Python Developers Egypt
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Portfolio

Portfolio

13656682
I developed an advanced AI-driven image analysis system for detecting and measuring structural cracks in walls and concrete surfaces. The system combines deep learning (YOLOv8 segmentation) with OCR-based ruler recognition and intelligent logic to differentiate between ruler and non-ruler images — delivering precise crack width measurements or symbolic estimates like <1 mm, <2 mm, <3 mm. ? Key Features: Automatic ruler vs non-ruler image classification using AI vision (ResNet-50 + OCR pattern analysis). Crack detection & width estimation using YOLOv8 segmentation and calibrated pixel-to-mm mapping. Smart report generation: auto-produces Word reports with annotated images and structured descriptions. Integrated detection of mould, dampness, spalling, and settlement defects. Optimized for deployment on Hugging Face Spaces or local environments (Python + Gradio). Lightweight, fast, and ready for civil inspection, construction monitoring, and safety auditing application

AI-Powered Structural Crack Detectio

13648818
This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

13646441

Production Line Optimization & Machi

13622552
I built a smart automation workflow that saves client information summaries directly to Google Sheets and instantly sends personalized email responses — all powered by n8n and AI models. Here’s how it works ? 1️⃣ When a client submits a form, the data automatically triggers the workflow. 2️⃣ The form data is passed to an AI model, which generates a structured summary or personalized message. 3️⃣ One branch saves the summary and key details to Google Sheets for easy tracking and organization. 4️⃣ Another branch uses Gmail integration to send an instant, customized reply to the client — no manual typing needed. This setup reduces repetitive admin work and ensures every client gets a quick, professional response while keeping your database updated in real time.

? Automating Client Communication

13621123
I just built a powerful AI-driven LinkedIn scraping workflow inside n8n, and I’m excited to share how it works! ⚙️ ? Goal: Automatically scrape and collect LinkedIn profile URLs from Google based on custom queries — all through an AI Agent, without manual searching. ? How It Works Trigger: The workflow starts “When a chat message is received” — you can simply message the bot with something like: “Find LinkedIn profiles of Python Developers in Egypt” AI Agent (Google Gemini Model): The request is sent to an AI Agent powered by Google Gemini Chat, which understands your intent and prepares a smart search query. SerpApi HTTP Request: The workflow then connects to SerpApi, which performs a Google Search and returns clean, structured JSON data containing the top LinkedIn profile URLs. Memory + Data Handling: A Simple Memory node keeps context from previous searches so the AI can refine or expand results on follow-up requests. Output: The workflow delivers a neat list of LinkedIn URL

? Automating LinkedIn Data Extracti

13617020
a clean, well-documented Python script that automatically gathers structured data from online sources and checking if the DNS available or not, and if the website allows scraping or not, saving in on e CSV Sheet the output correct data

Python scraping of more than 800 row

13656682
I developed an advanced AI-driven image analysis system for detecting and measuring structural cracks in walls and concrete surfaces. The system combines deep learning (YOLOv8 segmentation) with OCR-based ruler recognition and intelligent logic to differentiate between ruler and non-ruler images — delivering precise crack width measurements or symbolic estimates like <1 mm, <2 mm, <3 mm. ? Key Features: Automatic ruler vs non-ruler image classification using AI vision (ResNet-50 + OCR pattern analysis). Crack detection & width estimation using YOLOv8 segmentation and calibrated pixel-to-mm mapping. Smart report generation: auto-produces Word reports with annotated images and structured descriptions. Integrated detection of mould, dampness, spalling, and settlement defects. Optimized for deployment on Hugging Face Spaces or local environments (Python + Gradio). Lightweight, fast, and ready for civil inspection, construction monitoring, and safety auditing application

AI-Powered Structural Crack Detectio

13648818
This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

This project demonstrates my ability to solve real-world industrial engineering and production management problems using analytical reasoning and performance efficiency formulas. The task involved determining the number of machines required and their utilization rate for an industrial plant producing a single product across four process stages (A, B, C, D). Key parameters considered: Daily demand (400 units/day) Machine cycle times Availability, performance efficiency, and defect rates Daily 8-hour operation shift Final output: A precise, optimized solution showing the required machines and their utilization rates for each process — improving production planning accuracy and overall equipment effectiveness (OEE). ? Skills used: Industrial Engineering Calculations OEE (Overall Equipment Effectiveness) Operations Research & Line Balancing Problem Solving with Excel & Python Data Analysis for Production Optimization This portfolio item highlights my ability to quickl

Manufacturing System Efficiency

13646441

Production Line Optimization & Machi

13622552
I built a smart automation workflow that saves client information summaries directly to Google Sheets and instantly sends personalized email responses — all powered by n8n and AI models. Here’s how it works ? 1️⃣ When a client submits a form, the data automatically triggers the workflow. 2️⃣ The form data is passed to an AI model, which generates a structured summary or personalized message. 3️⃣ One branch saves the summary and key details to Google Sheets for easy tracking and organization. 4️⃣ Another branch uses Gmail integration to send an instant, customized reply to the client — no manual typing needed. This setup reduces repetitive admin work and ensures every client gets a quick, professional response while keeping your database updated in real time.

? Automating Client Communication

13621123
I just built a powerful AI-driven LinkedIn scraping workflow inside n8n, and I’m excited to share how it works! ⚙️ ? Goal: Automatically scrape and collect LinkedIn profile URLs from Google based on custom queries — all through an AI Agent, without manual searching. ? How It Works Trigger: The workflow starts “When a chat message is received” — you can simply message the bot with something like: “Find LinkedIn profiles of Python Developers in Egypt” AI Agent (Google Gemini Model): The request is sent to an AI Agent powered by Google Gemini Chat, which understands your intent and prepares a smart search query. SerpApi HTTP Request: The workflow then connects to SerpApi, which performs a Google Search and returns clean, structured JSON data containing the top LinkedIn profile URLs. Memory + Data Handling: A Simple Memory node keeps context from previous searches so the AI can refine or expand results on follow-up requests. Output: The workflow delivers a neat list of LinkedIn URL

? Automating LinkedIn Data Extracti

13617020
a clean, well-documented Python script that automatically gathers structured data from online sources and checking if the DNS available or not, and if the website allows scraping or not, saving in on e CSV Sheet the output correct data

Python scraping of more than 800 row

5.0 · 4 Reviews
Reviews
User Avatar

Python Multi-Knapsack Optimizer • $60 CAD

Quality of the work well hire Alhaitham Gamal M. again

GdevDataSceince

@GdevDataSceince

•

Flag of

Naogaon, Bangladesh

•

2 months ago

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PROFESSIONAL Mobile App Dev • $135 USD

He is very professional. Have all the needed technical skills, e.g. Python, Java, etc... I would love to work with him once again. Thanks:)

sanaaomrany

@sanaaomrany

•

Flag of

Cairo, Egypt

•

11 months ago

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RSA Algorithm Development in Python • $65 USD

I highly recommend Alhaitham Gamal M.HE PROVIDE A VERY PATIENCE AND RESPONSIVE SUPPORT

Mudassar H.

@researchvirtuoso

•

Flag of

FAISALABAD, Pakistan

•

1 year ago

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Project for Alhaitham M. • $12 USD

Absolutely satisfied. He provided excellent works, in particular at designing and image editing delivering tasks. Fast and Accurate. Will hire him once again. Tks:)

sanaaomrany

@sanaaomrany

•

Flag of

Cairo, Egypt

•

3 years ago

Share

Experience

Java Developer

Jan, 2024 - Present

•

1 year, 10 months

ATOS

Jan, 2024 - Present

•

1 year, 10 months

,I have strong knowledge and 3+ years of experience in N8N Workflows Automation/ Java/python /web scraping/bot development Blockchain/Django I worked at ATOS, and Qeema I developed many web apps using Django,python, python bots , Spring/Hibernate/OOP/JEE/Solidity apps you could check my Github: https://github.com/AlhaithamGamal ,I have a passion for learning a new technology I'm a quick learner

Flag of

Cairo, Egypt

Jan, 2024 - Present

•

1 year, 10 months

API Developer

Jan, 2019 - Feb, 2024

•

5 years, 1 month

Qeema

Jan, 2019 - Feb, 2024

•

5 years, 1 month

Working in adding and configure REST APIS or Python and Java Projects

Flag of

Cairo, Egypt

Jan, 2019 - Feb, 2024

•

5 years, 1 month

Bot Developer and Web Scraper

Jan, 2019 - Jan, 2024

•

5 years

Individual

Jan, 2019 - Jan, 2024

•

5 years

Working on self-projects of web scraping and creating Telegram Bots using Python

Flag of

Cairo, Egypt

Jan, 2019 - Jan, 2024

•

5 years

Education

Ain Shams University

2015 - 2018

•

3 years

Very Good

Flag of

Egypt

2015 - 2018

•

3 years

Qualifications

Ecommerce System

2025

Self

Ecommerce Systems using N8N /Workflows,Automation and Python

2025

Web Scraping

2024

individual

Web Scraping using Python

2024

Java

2018

Java

java oop jee

2018

Publications

Ecommerce Django

Self

Complete Python Django web app for buying and selling products

Twitter api data wrangling

Me

data of a rating dog account on twitter gathered, assessed and cleaned by using python/pandas/numpy)

Ecommerce spring

Me

(Ecommerce Java Web application using Spring boot/Angular/Hibernate/REST/MVC/MySQL/SQL)

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