• Design and build AI pipelines using frameworks like LangGraph, CrewAI, n8n, and LangChain to create modular, testable, and composable agents. • Build and scale RAG, Graph-RAG, and custom fine-tuned LLM solutions for real estate data normalization, enrichment, summarization, and analytics. • Develop agent patterns that can reason over tools, retrieve context, and persist goals—bringing multi-step reasoning and tool execution logic to life. • Collaborate with engineers, product managers, and domain experts to turn exploratory POCs into robust production systems. • Contribute to internal frameworks and standards for evaluating and debugging agents (e.g., using LangFuse, OpenTelemetry, or custom traces). • Drive continuous experimentation with memory systems, vector search, and knowledge graph integration for dynamic personalization and logic-based chaining. • Participate in agent simulation testing and contribute to establishing MCP (Modular Control Plan)-based design strategies for safe and reusable AI behaviors.