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Vamshikrishna Bandi
Senior AI/ML Engineer specializing in Generative AI and agentic multi-agent systems
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About
Built and shipped a production LLM-powered multi-agent RAG system to automate complex internal support workflows, integrating tool execution (SQL/APIs) with validation guardrails to reduce hallucinations. Optimized for real-world latency and cost via model routing, caching, and async parallel tool calls, and enforced reliability with CI-gated golden test sets derived from anonymized production queries.
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Key Strengths
- Built and deployed a production LLM agent system automating complex internal workflows
- Strong RAG + multi-agent architecture design (planner/retriever/executor/validator)
- Reliability focus: hallucination mitigation via grounding rules and validation layer
- Performance optimization: reduced model calls, async/parallel tool execution, retrieval optimization
- Cost optimization: model routing, caching, early stopping to prevent token waste
- Rigorous evaluation approach using golden test sets from anonymized real queries and CI release blocking
- Effective collaboration with non-technical stakeholders through workflow discovery, demos, and translating requirements into tests
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