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Meet Merchant
Mid-level Software Engineer specializing in LLM agents and full-stack systems
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At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.
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Key Strengths
- Built and deployed an LLM-powered WebGIS assistant framework integrated with ArcGIS JS SDK
- Designed modular multi-agent architecture with extensibility for third-party custom agents
- Strong reliability engineering for LLM systems (strict tool calling, live-state validation, guardrails)
- Production-grade observability and evaluation (LangSmith tracing, offline evals, accuracy/latency tracking)
- Cost/performance optimization via model comparisons and selective use of cheaper/faster models
- Token and context optimization using embeddings + cosine similarity to shortlist relevant fields
- Cross-functional collaboration with GIS product/domain expert and incorporation of user feedback
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