Enterprises are rapidly deploying large language models, retrieval augmented generation pipelines, and tool using agents into production, often on shared high performance computing clusters and cloud accelerator platforms that also support defensive analytics. These systems increasingly function not as isolated models but as AI estates: socio technical systems spanning models, agents, data pipelines, security tooling, human workflows, and hyperscale infrastructure. Existing governance and security frameworks, including the NIST AI Risk Management Framework and systems security engineering guidance, articulate principles and risk functions but do not provide implementable architectures for multi agent, AI enabled cyber defense. This paper introduces the Practitioners Blueprint for Secure AI (PBSAI) Governance Ecosystem, a multi agent reference architecture for securing enterprise and hyperscale AI estates. PBSAI organizes responsibilities into a twelve domain taxonomy and defines bounded agent families that mediate between tools and policy through shared context envelopes and structured output contracts. The architecture assumes baseline enterprise security capabilities and encodes key systems security techniques, including analytic monitoring, coordinated defense, and adaptive response. A lightweight formal model of agents, context envelopes, and ecosystem level invariants clarifies the traceability, provenance, and human in the loop guarantees enforced across domains. We demonstrate alignment with NIST AI RMF functions and illustrate application in enterprise SOC and hyperscale defensive environments. PBSAI is proposed as a structured, evidence centric foundation for open ecosystem development and future empirical validation.

翻译：企业正在迅速将大型语言模型、检索增强生成流水线以及工具使用智能体部署到生产环境中，这些系统通常运行在共享的高性能计算集群和云加速器平台上，这些平台同时也支持防御性分析。这些系统日益不再作为孤立的模型运行，而是作为AI资产：一种涵盖模型、智能体、数据流水线、安全工具、人工工作流和超大规模基础设施的社会技术系统。现有的治理和安全框架，包括NIST人工智能风险管理框架和系统安全工程指南，阐述了原则和风险功能，但并未为多智能体、AI赋能的网络防御提供可实施的架构。本文介绍了安全AI实践者蓝图治理生态系统，这是一种用于保护企业和超大规模AI资产的多智能体参考架构。PBSAI将职责组织成一个包含十二个领域的分类体系，并定义了有界的智能体家族，这些家族通过共享上下文封装和结构化输出合约在工具与策略之间进行协调。该架构假设了企业基线安全能力，并编码了关键的系统安全技术，包括分析监控、协同防御和自适应响应。一个关于智能体、上下文封装和生态系统级不变量的轻量级形式化模型，阐明了跨领域执行的追溯性、来源和人在回路保证。我们展示了与NIST AI RMF功能的一致性，并说明了其在企业安全运营中心和超大规模防御环境中的应用。PBSAI被提议作为一个结构化、以证据为中心的开放生态系统开发和未来实证验证的基础。