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shiva kumar kotha
Mid-level AI/ML Engineer specializing in Generative AI and healthcare data
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Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.
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Key Strengths
- Built and deployed a production RAG document Q&A system end-to-end (ingestion → embeddings → vector search → API)
- Performance optimization for large documents via streaming ingestion and parallel chunking
- Improved retrieval and answer quality through systematic tuning of chunking, embedding models, and prompts (few-shot + structured instructions)
- Production reliability focus: logging, monitoring, retries, and unit tests
- Data pipeline orchestration across ADF, Databricks, and Synapse with scheduling/monitoring for timely, high-quality data delivery
- Effective collaboration with non-technical business stakeholders using prototypes and feedback loops
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