Define the architecture for an enterprise AI Engineering Harness including LLM Gateway, Prompt Management, Context Management, RAG Platform, Knowledge Graph, Vector Database, MCP Servers, AI Memory, Workflow Orchestration, Agent Registry, Tool Registry, Policy Engine, Observability, Evaluation Framework, Model Gateway, Security Framework, Model Routing, and Enterprise Knowledge Integration. This leader will define the architecture, engineering practices, governance, platforms, and adoption strategy required to embed AI agents throughout the Product Development Life Cycle (PDLC), enabling engineers, product managers, QA, DevOps, security, validation, and operations teams to work alongside autonomous AI agents.