As organizations move from standalone LLM applications to complex, agentic AI workflows, LLMOps becomes the critical backbone enabling scale, reliability, and trust. This session explores how to design robust LLMOps frameworks to build, monitor, and govern multi-agent systems in production. It will cover practical approaches to orchestration, observability, evaluation, cost control, and risk management, along with governance strategies to ensure compliance, safety, and responsible AI at scale. Attendees will leave with actionable insights to operationalize agentic AI systems that are resilient, transparent, and enterprise-ready.