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Sri Tenali
Mid-level Software Engineer specializing in FinTech backend systems
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About
Built and deployed an AI-driven expense categorization workflow integrating OpenAI API and PGVector to automate general ledger coding. Stands out for combining LLM/embedding architecture with finance operations context, stakeholder-facing deployment ownership, and measurable impact of roughly 30%+ reduction in manual coding effort.
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Key Strengths
- Owned end-to-end deployment of AI-powered expense categorization
- Built production LLM workflow using OpenAI API and PGVector
- Translated finance business requirements into automated GL coding logic
- Reduced manual GL coding overhead by roughly 30%+
- Strong stakeholder management with product, finance, and engineering teams
- Used iterative demos and feedback loops to align AI behavior with business needs
- Debugged non-deterministic AI/data pipeline incidents using logs and baseline comparisons
- Mitigated production issues with backfill recategorization and pipeline hardening
- Designed validation and error-handling workflows for messy OCR-extracted inputs
- Applied schema enforcement with Pydantic for backend reliability
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