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sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
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About
Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.
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Key Strengths
- Built and deployed a production LLM university chatbot using RAG to reduce support volume
- Strong hallucination-mitigation approach (RAG + confidence checks + clarification questions)
- Latency and reliability optimization via caching and iterative prompt/model/retrieval tuning
- Data pipeline reliability engineering with Airflow (sensors, retries, alerts) to handle late-arriving files
- Metrics-driven evaluation of AI workflows (accuracy, task success rate, latency) with offline tests, unit/integration tests, and A/B rollouts
- Effective collaboration with non-technical stakeholders through prototypes and feedback-driven iteration
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