Ahmad Dlahmea

I’m an Applied AI / Backend Engineer focused on building reliable AI-native products. I design AI agents and RAG workflows that turn unstructured knowledge into structured, source-grounded answers.

In my AI engineering internship in Germany, I built an AI-assistant architecture combining a Smart Router, SQL Agent, and RAG Agent. I applied prompt engineering, tool calling, document chunking, embeddings, and semantic search to deliver dependable LLM workflows.

On the backend side, I worked with Python, FastAPI, and REST APIs, including session integration, testing/QA, and clear technical documentation. I also compared ChromaDB and Milvus to evaluate vector retrieval approaches with traceability and failure handling in mind.

Before that, I completed a Computer Hardware / IT Consulting internship supporting clients with Microsoft 365, Intune, and Autopilot. I bring this product-and-handover mindset to projects like my Streamlit GJU Regulations Assistant, the Therabot therapy chatbot, and a PyTorch plant disease recognition model.