Worked on the BerriAI/litellm repository to enhance the reliability of Bedrock-backed batch processing by addressing a critical bug in the batch ID retrieval flow. Focused on backend and API development using Python, the work ensured that the correct model was consistently passed to the Bedrock-encoded batch retrieval function, preventing misrouting and reducing runtime errors. The approach included refining error messaging for clarity, reinforcing provider configuration loading to avoid unnecessary fallbacks, and adding targeted tests to improve coverage of Bedrock workflows. These changes collectively stabilized end-to-end batch processing and contributed to a reduction in support tickets related to retrieval issues.