Developed the Finance SEC Search Resource Server for the NVIDIA-NeMo/Gym repository, enabling automated search and analysis of SEC filings using large language models. The solution introduced an end-to-end backend pipeline in Python, integrating API development and data parsing to support regulatory research and financial analysis. By building and connecting the Finance Agent Environment, the work streamlined the download, parsing, and retrieval of financial documents, reducing manual research time and supporting scalable, data-driven workflows. The architecture demonstrated effective backend design and machine learning integration, laying a foundation for automated due diligence and regulatory compliance within finance-focused research environments.