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AI Engineer - LLM systems running agentic workflows on AWS infrastructure
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AI Engineer - LLM systems running agentic workflows on AWS infrastructure

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Mo-Abdelhameed/README.md

Mohamed Abdelhamid

AI Engineer in Cairo, Egypt. I build LLM systems — agentic workflows, RAG pipelines, semantic search — along with the backend services and AWS infrastructure that keep them running in production.

Three years at Ready Tensor, an AI publication and certification platform.

What I work on

Backend and infrastructure for AI products. I owned the backend and cloud architecture for Clyep, a platform that turns a PowerPoint or PDF into a fully narrated, animated explainer video. FastAPI services on ECS Fargate, long-running render jobs on AWS Batch, Aurora PostgreSQL for persistence, ElevenLabs for narration, everything provisioned as infrastructure as code with AWS CDK.

Agentic systems and retrieval. Multi-agent evaluation pipelines, semantic search over pgvector, and a fair amount of time spent on the unglamorous part: figuring out when retrieval is quietly failing rather than when it obviously is. Benchmarked naive RAG, agentic RAG, and HyDE on a real evaluation workload.

Teaching what I build. I authored and presented curriculum for two AI engineering certification programs used by 30,000+ learners.

Selected work

Most of the repositories here are open ML model implementations built during my time at Ready Tensor, spanning tabular classification and regression, time series forecasting, and text and image classification.

Papers

Tools

Python · FastAPI · PyTorch · LangChain · LangGraph · Hugging Face · pgvector · PostgreSQL · Docker · AWS (CDK, ECS Fargate, Batch, Lambda, Bedrock, SageMaker, S3)

Contact

LinkedIn · mohamedabdelhamid3030@gmail.com

Open to remote AI engineering roles.

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