Architect and build next generation autonomous AI workflows operating at intersection of Software Engineering, Data Engineering, and Machine Learning. Design production-grade Agentic Systems - intelligent applications capable of reasoning, planning, and executing complex tasks autonomously. Lead hands-on design and coding of stateful multi-agent workflows using Python and orchestration frameworks like LangGraph, CrewAI, or AutoGen. Design Agent-to-Agent communication protocols, engineer robust control flows and state management, implement Model Context Protocol for universal interfaces. Build agent data pipelines, ensure real-time context injection, implement comprehensive observability using LLMOps and tracing tools. Requires 7+ years technical experience with 2+ years building LLM-based applications in production. Experience with Vector Databases, cloud architecture, Kubernetes, Docker, and advanced Python proficiency essential.