The ideal candidate should be capable of building scalable AI platforms from end to end, including data ingestion, embedding pipelines, retrieval systems, agent workflows, model serving, API layers, UI/UX integration, monitoring, security, and production deployment across multi-cloud environments. The role requires strong hands-on experience across LLMs, RAG, Graph RAG, multi-agent orchestration, vector databases, MCP setup, full-stack application development, cloud-native deployments, observability, and data engineering pipelines.