Mohamed WhdanAI Engineer & Full Stack Developer
Email
whdan236@gmail.com
Phone
01069217634
Location
Egypt - Kafr El Sheikh [Ready to Relocate]
2002-06-23
Exempted
LinkedIn
LinkedIn
GitHub
GitHub
Portfolio
PROFILE

Collaborated with 40+ companies and individuals to deliver, production-ready AI solutions

With "4+ years" of experience in AI Engineering and Software System Design, I have developed and deployed end-to-end projects while working as a Generative AI Engineer, Computer Vision Engineer, Full-Stack Developer, and DevSecOps Engineer Cloud Engineer. I have worked as both a freelancer and with many companies across different countries, giving me hands-on experience, strong problem-solving skills, and the professionalism needed to contribute effectively in large tech organizations.

SKILLS
AI & Data Science

Computer Vision - Machine Learning - Deep Learning - Speech Recognition - Reinforcement Learning - NLP

Frameworks

TensorFlow - PyTorch - Scikit-learn - Pandas - NumPy - SciPy - Matplotlib - Seaborn - OpenCV - Librosa - Pygame / Baseline

Cloud (AWS & Azure)

SageMaker - Bedrock - Comprehend - Rekognition - Polly - Transcribe - Translate - Textract - Lex - Kendra - Forecast - Personalize - S3 - Lambda - RDS - DynamoDB - API Gateway - CloudWatch - IAM - EC2 - SQS - Azure DevOps

System Design & Software Engineering

Scalable Architecture - Distributed Systems - Event-Driven Architecture - High Availability (HA) - Fault Tolerance - Load Balancing - Caching Strategies - Database Sharding - Database Replication - Asynchronous Processing - Message Queues - API Versioning - Rate Limiting

Frontend Development

Angular - React - HTML5 - CSS3 - JavaScript ES6+ - TypeScript - AJAX - Bootstrap - Tailwind - Sass - jQuery - XML - Razor Pages

Testing & API Tools

Unit Testing - Load Testing - Pytest - Locust - Web API - Postman - Swagger / OpenAPI

DataBase

SQL – SQLite - PostgreSQL – MongoDB / Motor – Redis – Firebase - Query Optimization - ORMs: (SQLAlchemy – Alembic)

Generative AI

NLP - Prompt Engineering - LLMs - RAG - AI Agents - Agentic AI - n8n - MCP - LangChain - LangGraph - LlamaIndex - Finetuning - CrewAI - AutoGen - smolagents - Vector Database (Faiss / Pinecone / Chroma / Weaviate/ Qdrant) - Pydantic - Transformers - Hugging Face - LLM Evaluation (TruLens / DeepEval / ragas) - VertexAI - Neo4j (Knowledge Graph) - LLMOps - vLLM - AirLLM - LiteLLM - Voice Agents (LiveKit / Deepgram) - Data Extraction (Docling / Unstructured.io)

MLOps & DevOps

FastAPI - Streamlit / Gradio - Docker - Kubernetes -Terraform - Prometheus / Grafana - GitHub Actions - Kafka - LangSmith - Langfuse - AgentOps - Helm - Nginx - Linux - Bash - SSH - GitLab CI/CD

Data Analysis

Power BI – DAX – Power Query Excel – PivotTables – Power Pivot – MySQL

Backend Development

FastAPI – Flask - Uvicorn - Pydantic - AsyncIO - C# – .NET Core – .NET Framework – .NET Core Web API – .NET Core MVC - LINQ - JWTAuthentication - (Node.js & Express.js) - (Deno.js & Oak.js) - Drizzle - Dependency Injection - SignalR - gRPC - Entity Framework

Programming Languages

Python / C++ / Java / C# / JavaScript

Additional Technologies

Jira - Web Scraping (Selenium / BeautifulSoup / Scrapy / Requests) - Crawl4AI - Networking (WebSocket / WebRTC) - Git & GitHub - Security - Networking

Mohamed Whdan
PROFESSIONAL EXPERIENCE

Red Sea Global & DXC Technology⁠

AI Software Engineer | Full Time
  • Designed and deployed enterprise-scale microservices and AWS cloud solutions capable of supporting millions of users, applying advanced system design principles for scalability and high availability.
  • Jan 2025 – Aug 2026Remote, United States
  • Led end-to-end development as the sole engineer, owning system architecture, backend development, cloud infrastructure, DevOps, and production deployment.
  • Built and integrated enterprise APIs using MuleSoft and AWS services, improving system reliability, maintainability, and cross-platform interoperability.
  • Phoenix Consulting (AWS Partner)⁠

    Data Scientist | Full Time
  • Certified Cloud Practitioner & Certified AI/ML Practitioner
  • Jun 2025 – Aug 2025Hybird, Cairo
  • Built and deployed scalable Multi Agent Systems using Amazon SageMaker and Bedrock.
  • Applied Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to solve advanced NLP tasks.
  • Implemented MLOps practices including CI/CD, model monitoring, versioning, and automated deployment pipelines.
  • 绿心 - LVXIN⁠

    AI Engineer & Full Stack Developer | Contract
  • Developed an AI-powered legal analytics system for contract analysis and risk detection using NLP and Alibaba APIs.
  • May 2025 – Jun 2025Remote, China
  • Achieved 99.9% accuracy, enabled 24/7 automation, and reduced manual review time by 90%.
  • Delivered insights in under 5 minutes, significantly boosting legal team efficiency.
  • PraxiLabs⁠

    Generative AI Engineer
  • Integrated AI Agents into 5+ Unity applications using LLMs, RAG, multi-agent architectures, and tool calling, delivering AI-powered learning experiences for 10,000+ undergraduate students.
  • Oct 2025 – Aug 2026Hybird, Dokki
  • Developed a multi-agent AI assistant supporting 150+ university courses across Egyptian universities, providing accurate, context-aware responses using RAG and external AI tools.
  • Designed and deployed scalable AI backend services and cloud integrations, reducing response latency by 30% and supporting real-time, production-scale AI interactions.
  • Quantum Bit

    AI Engineer | Full Time
  • Developed ML models for options trading and stock price prediction, improving forecasting accuracy by identifying key market signals.
  • Oct 2024 – Jun 2025Remote, Saudi Arabia
  • Performed in-depth data analysis to uncover trends and built optimized investment portfolios based on risk/reward profiles.
  • Focused on forecasting, risk assessment, and investment strategy development using time-series analysis and supervised learning techniques.
  • MedicaProf⁠

    AI Engineer | Part Time
  • Built AI agents for intelligent automation and interaction with n8n.
  • Sep 2025 – Jan 2026Remote, Paris
  • Worked with AWS and Microsoft Azure for cloud-based AI deployment and services integration.
  • Mohamed Whdan
    PROJECTS

    Chat With Your Data⁠

    LLM & RAG System with API Integration

    Designed and deployed a scalable multimodal RAG platform handling 1TB+ of heterogeneous data (text, documents, images, and structured data). Built 2 REST APIs for automated ingestion and AI-powered querying, integrating data processing, vector search, and fine-tuned LLM pipelines to deliver real-time, context-aware responses while reducing manual analysis efforts by 80%+.

    Jul 2025 – Present

    Tools: LLMs - RAG – LangChain – LlamaIndex – Vector Databases – Chroma – Prompt Engineering – Text Embedding – Data Cleaning – NLP

    Real-Time Multilingual Emergency Call Translation System⁠

    An AI solution for bridging language barriers during Hajj emergencies

    During the Hajj season in Saudi Arabia, many pilgrims from different nationalities arrive to perform Hajj, and a large number of emergency cases occur. In many situations, callers cannot be understood because they speak different languages or speak very fast. Because of this problem, the Saudi Ministry of Hajj and Umrah contacted me to build a system that translates speech in real time on both sides of the call.

    Nov 2025 – Dec 2025

    I built a fast and powerful system using open-source AI models that supports Arabic, English, French, Urdu, and Indonesian, and I also added a call analysis module that stores each emergency call in the database after it ends.

    Tools: OpenSource -Finetuning - (TTS, LLMs, STT) - Websocit - Llama.cpp

    Built a Text-to-SQL AI Agent that converts natural language queries into SQL with 95%+ query accuracy using dynamic database schemas. Developed secure query execution, data visualization, authentication, and role-based access control with 100% permission enforcement to ensure authorized data access only.

    May 2025 – Jun 2025

    Tools: FastAPI - Chart.js - Custom tools - LangGraph - Chroma Server

    Autonomous self-driving Car for Egyptian streets⁠

    Autonomous self-driving vehicle using V2X Communication (V2V and V2I)

    Developed a computer vision system for autonomous driving in Egyptian streets using 5,000+ images and 6 AI models for lane detection, obstacle avoidance, and traffic sign recognition. Achieved 92%+ detection accuracy with real-time decision-making across multiple driving scenarios.

    Jun 2023 – Aug 2024

    Tools: OpenCV – TensorFlow – PyTorch – Computer Vision – Generative AI

    EDUCATION

    Bachelor of Computer Science

    Benha University

    Al Specialization

    Aug 2020 – Aug 2024Benha, Egypt

    Web API - MVC - DataBase - C# - Angular

    Nov 2024 – May 2025Port Said, Egypt
    LANGUAGES
    Arabic — Native/Bilingual
    English — Fluent ( C1 )
    Japanese — Elementary
    Mohamed Whdan