Developed a security enhancement for the BerriAI/litellm repository by integrating Cycraft XecGuard into the LLM pipeline, enabling multi-policy scanning and context grounding validation for large language model applications. This feature, implemented in Python, focused on strengthening risk controls and supporting regulatory compliance for enterprise LLM deployments. The work demonstrated skills in API integration, backend development, and security best practices, with an emphasis on DevSecOps principles and unit testing. By providing clear commit traceability, the enhancement improved auditability and robustness of the LLM workflow, addressing the need for safer, more compliant AI systems without introducing new bug fixes during the period.