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Nikhitha santhoshi Maroju
Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices on AWS
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Built and shipped a production LLM-powered fraud investigation agent using RAG to generate transaction explanations and draft analyst reports. Emphasizes production robustness (fallbacks, strict structured outputs, async orchestration, monitoring/evals) and reports measurable impact: ~12% precision lift and ~80 high-priority alerts per week with reduced manual effort.
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Key Strengths
- Shipped production LLM assistant for fraud investigation with RAG and analyst report generation
- Designed reliability via graceful fallbacks so core signals work without the LLM
- Implemented strict schemas/validated JSON structured outputs to reduce hallucinations and improve downstream reliability
- Built async orchestration with intermediate state/checkpoints enabling safe retries without restarting the workflow
- Established eval/monitoring loops (offline labeled evals + online latency/error/fallback metrics) and iterated to reduce invalid outputs
- Delivered measurable impact: ~12% detection precision improvement and ~80 high-priority alerts/week while reducing manual effort
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