Ahmed M.

Architecting production-grade AI systems, LLM workflows, and high-performance machine learning pipelines that drive measurable ROI. With 7+ years of experience engineering enterprise AI solutions at scale—including work with leading telecom and cloud infrastructures—I specialize in building intelligent applications that bridge cutting-edge AI with rock-solid reliability. Whether you need to deploy advanced RAG architectures, custom agentic workflows, or high-throughput predictive models, I build scalable systems designed for production from day one. What I Deliver: Generative AI & Agentic Systems: Production RAG pipelines, hybrid search, reranking (RRF), fine-tuning (PEFT/LoRA), and autonomous agent architecture using LangChain, LangGraph, and ReAct frameworks. Machine Learning & Predictive Modeling: End-to-end ML lifecycle management, time-series forecasting, and classification/regression engines utilizing PyTorch, TensorFlow, Scikit-Learn, and XGBoost. MLOps & Backend Engineering: Scalable containerization and deployment via FastAPI, Docker, MLflow, Airflow, and Azure AI Foundry/Databricks. Data Architecture: High-volume data processing and distributed computing using PySpark, SQL, BigQuery, and vector databases (ChromaDB, Pinecone).