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Vamshikrishna Chitturi
Mid-level AI Engineer specializing in Generative AI, LLM fine-tuning, and RAG systems
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About
Built and deployed production LLM applications including a natural-language-to-read-only-SQL system focused on ambiguity handling and query safety (schema whitelisting, intent validation, confidence checks, deterministic execution). Experienced with LangChain-based, modular agent orchestration and RAG document QA for large PDFs, with a metrics-driven testing/evaluation approach and cross-functional delivery with marketing on an AI content recommendation/search tool.
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Key Strengths
- Built and deployed production LLM system translating natural language to read-only SQL with safety controls
- Mitigates hallucinations via constrained, multi-step workflows (role/output constraints per step)
- Designs schema-aware prompting with strict whitelisting to prevent unsafe/invalid queries
- Implements intent validation and confidence checks before executing generated queries
- Orchestrates modular agent workflows using LangChain (templates, routing, memory)
- Strong testing and evaluation practice: unit + E2E + edge-case prompts; uses accuracy/precision/recall and user-centric metrics
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