Medhat Elhady
Verified Expert in Engineering
AI Engineer and Developer
6th of October City, Giza Governorate, Egypt
Toptal member since July 8, 2026
Medhat is an AI engineer with 3+ years of experience designing and deploying machine learning and generative AI solutions. His expertise spans AWS, Terraform, and MLOps automation, with notable work at RackSpace and Telecom Egypt. Medhat reduced ML deployment time by 70% through automated Terraform workflows and led migrations to Amazon SageMaker for improved resource management.
Portfolio
Experience
- Python - 5 years
- SQL - 4 years
- Generative Artificial Intelligence (GenAI) - 3 years
- Amazon SageMaker - 3 years
- Machine Learning Operations (MLOps) - 3 years
- Terraform - 2 years
- Small Language Models (SLMs) - 2 years
- vLLM - 1 year
Preferred Environment
Docker, Terraform, Jenkins, Streamlit, AWS Bedrock AgentCore, Amazon SageMaker, RAG Systems, Agentic AI, Machine Learning
The most amazing...
...workflow I've built is an automated Terraform deployment on Amazon SageMaker that reduced ML model deployment time by 70%.
Work Experience
Data Scientist | AI/ML Engineer
Rackspace Technology
- Built an automated Terraform workflow to deploy ML models on Amazon SageMaker endpoints, reducing deployment time by 70%.
- Architected a drift detection agent that relies on retrieval-augmented generation (RAG) and device incidents to identify risks on devices and suggest remediation.
- Fine-tuned Amazon Titan and Cohere LLM on Amazon Bedrock to prototype an automated code-generation system, enabling rapid generation of boilerplate code and reducing effort for business users.
- Migrated multiple teams from JupyterHub to Amazon SageMaker environment and implemented team-level isolation, S3 access controls, and instance provisioning, improving resource management and security compliance across teams.
- Contributed a feature enhancement to the open-source Terraform AWS Provider (HashiCorp).
Mentor
Udacity
- Worked for three years on the FWD initiative in the data analysis track and the DECI initiative, teaching Programming Fundamentals Level 2.
- Reviewed student projects and provided feedback on areas for improvement, as well as suggestions for enhancing their work in fields of generative AI, agentic systems, and Amazon Bedrock.
- Answered 1,500+ questions, created 50+ articles, conducted over 40 webinars and more than 100 sessions, and reviewed 2,000+ projects in the field of data, generative AI, and programming.
BI and Data Warehouse Specialist
Telecom Egypt
- Migrated real-time cabinet-level outage data into the customer service portal, enabling automated customer notifications and reducing customer agent workload by 40%.
- Developed and maintained ETL processes that transform data from its raw form into a format that can be easily analyzed and visualized using SQL and Talend ETL.
- Engineered a sentiment analysis proof of concept to automatically classify customer reviews for marketing campaigns.
Experience
Find Donors for Charity | Machine Learning Classification Project
https://github.com/medhatelhady/Find-Donors-for-CharityMLDog Image Classifier with AWS
https://github.com/medhatelhady/dog-images-classifier-using-awsRAG Application with Amazon Bedrock
https://github.com/medhatelhady/Building-Generative-AI-Applications-with-Amazon-Bedrock-and-pythonEducation
Bachelor's Degree in Computer Engineering
Zagazig University - Zagazig, Egypt
Certifications
AWS Certified Generative AI Developer – Professional
Amazon Web Services
Machine Learning in Production
DeepLearning.AI
AWS Certified Machine Learning – Specialty
Amazon Web Services
AWS Machine Learning Engineer Nanodegree
Udacity
Machine Learning
Coursera
AI Programming with Python Nanodegree
Udacity
Skills
Libraries/APIs
PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, Matplotlib, vLLM, Keras, XGBoost
Tools
Terraform, Amazon SageMaker, Talend ETL, Git, GitLab, AWS IAM, Seaborn, Jenkins, Jupyter
Languages
Python, SQL, Bash
Frameworks
LangGraph, Agentic Frameworks, Streamlit
Platforms
Amazon Web Services (AWS), Docker, LangSmith, Langfuse, AWS Lambda, Linux
Paradigms
Model Context Protocol (MCP), Anomaly Detection
Storage
Databases
Other
RAG Systems, Agentic RAG Systems, Transformers, LangChain, Prompt Engineering, Fine-tuning, EDA, Data Modeling, Deep Learning, Natural Language Processing (NLP), Data Processing, Feature Engineering, Model Evaluation, Terraform (IaC), CI/CD Pipelines, Agentic AI, Artificial Intelligence (AI), Applied AI, Large Language Models (LLMs), Large Language Model Operations (LLMOps), Data Science, AI Agents, AI Agent Orchestration, OpenAI, RAG Architecture, Conversational AI, Performance Optimization, Monitoring, Agentic AI Systems, Agentic Workflow Design, Retrieval-augmented Generation (RAG), Inference Optimization, Web Scraping, Machine Learning, Data Structures, Algorithms, Small Language Models (SLMs), LLM Fine-tuning, Amazon Bedrock AgentCore, Model Validation, Machine Learning Operations (MLOps), Data Analysis, Generative Artificial Intelligence (GenAI), AI Programming, Hyperparameter Tuning, Data Augmentation, Computer Vision, Amazon RDS, Embedding Models, Deep Neural Networks (DNNs), Deployment, Observability, Supervised Learning, Clustering
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