Developed and delivered the Arthur AI Guardrail Integration for LLM Request Validation within the arthur-ai/arthur-engine repository, focusing on enhancing the security and reliability of LLM workflows. The work involved integrating Arthur AI as a custom guardrail on the TrueFoundry AI Gateway, enabling validation of both inputs and outputs for large language model requests. This approach reduced the occurrence of invalid requests and mitigated security risks. The implementation leveraged Python and FastAPI for API development and integration, with comprehensive documentation provided in Markdown. The project was feature-driven, with no major bugs reported, reflecting a focused and robust engineering effort.