Fadil Awan

Build and deploy production AI services including document automation, RAG, and multimodal inference using Python, FastAPI, and Docker. Engineer RAG pipelines and agentic workflows with LangGraph, tool calling, and MCP, and build LLM and RAG regression suites with LangSmith and Langfuse tracing.

Build adaptive NPC decision and difficulty systems in Unity and C# that adjust in-game behavior in real time from player telemetry. Profile and optimize Unity and C# model inference for constrained edge and mobile hardware.

Owned the full ML workflow from raw data to validated, monitored models across forecasting, classification, clustering, and anomaly detection. Engineered feature pipelines with cross-validation, experiment tracking, and model monitoring for reproducible inference.

Built ETL and automated reporting pipelines that transformed heterogeneous operational data into analytics-ready datasets and downstream ML inputs.

Pursuing a Bachelor of Science in Data Science and Artificial Intelligence, expected to graduate in 2026.