Senior Principal EA Applied AI Agentic Architecture

Responsibilities

• Defines and owns enterprise reference architectures and design standards for applied AI, GenAI, and Agentic AI systems deployed into clinical, research, operational and administrative workflows.
• Architect Agentic AI and multi-agent system (MAS) patterns appropriate for enterprise and regulated clinical use, including agent orchestration, human-in-the-loop controls, and safety boundaries.
• Owes applied GenAI integration architecture including retrieval-augmented generation (RAG), prompt governance frameworks, LLM orchestration patterns, and API consumption standards across enterprise AI platforms.
• Establishes and maintains responsible AI guardrails, clinical AI safety frameworks, and applied AI risk controls, ensuring alignment with patient safety obligations and regulatory requirements.
• Represents in governance of AI use-case portfolio from an architecture perspective, including use-case value-cost-risk analysis, clinical applicability assessment, and architecture review for AI solutions entering production.
• Led AI architecture scenario planning to anticipate regulatory, clinical safety, and technology risks, and embeds adaptive guardrails into enterprise AI architecture standards and governance frameworks.
• Applies human centered design and design thinking principles to AI architecture, ensuring solutions are aligned to end user needs, workflow integration, and the patient and clinician experience.
• Partners with clinical informatics, digital health, data & analytics and operational leaders to translate AI investments into architecturally sound, measurable enterprise outcomes.
• Develops and enforces enterprise AI consumption standards and integration patterns for EHR systems, clinical applications, operational platforms, and enterprise data services.
• Collaborates with Information Security, Privacy, Legal, Compliance, and Risk Management to ensure AI use cases meet HIPAA, patient safety, and applicable regulatory and audit requirements.
• Provides architecture advisory and review for AI-related vendor evaluations, procurement decisions, and enterprise product selections at the solution and workflow layer.
• Serves as a senior architectural thought leader and trusted advisor to executive, clinical, and operational stakeholders on applied AI architecture matters.

Qualifications

• Certified Machine Learning, Professional ML Engineer, AI Governance, or equivalent AI certification is preferred.
• Bachelor's Degree is required.
• 10+ years Information Technology (IT) experience, with 7+ years Enterprise Architecture is required.
• 3+ years AI and Agentic AI Architecture is required.