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Atharva Joshi
Mid-level GenAI Engineer specializing in RAG systems and AI agents
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LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.
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Key Strengths
- Architected and deployed an MCP-driven LLM solution integrating Neo4j + Elasticsearch with ChatGPT UI
- Improved response latency ~60% (1300ms to 600ms) via TTL-based caching of static schema/business context
- Solved accuracy issues by formalizing business definitions (data dictionary) to reduce LLM attribute confusion
- Built multi-agent workflow automation (e.g., SQL generator/validator agents) from request intake through PR creation
- Uses iterative build-evaluate-improve approach for agent/workflow reliability
- Strong collaboration with non-technical stakeholders using visuals and analogies to explain complex AI concepts
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