Principal Architect - Gen AI

Telecommuter TN

R78346

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The Gen AI Principal Architecture within the Transformation Office serves as the enterprise executive accountable for AI architecture strategy, governance, and platform direction—driving large-scale business transformation through applied Generative AI, Agentic AI, and advanced intelligence capabilities. This role establishes and evolves the enterprise “intelligence layer” as a strategic capability, ensuring AI is delivered securely, ethically, and at scale across the organization’s Lines of Business, shared services, and core technology ecosystem.

Operating at the intersection of enterprise architecture, product/platform strategy, risk governance, and execution oversight, this leader defines the end-to-end architectural vision and operating model for LLM-powered platforms, agentic systems, and conversational/automation capabilities. The role influences enterprise prioritization and investment decisions, sets cross-functional standards, and ensures AI capabilities integrate effectively with legacy and modern environments across AWS and Azure, translating complex AI innovation into measurable business value and operational outcomes.

• Owns and sets the enterprise Generative AI and Agentic AI architecture vision and multi-year roadmap, aligning to enterprise strategy, transformation priorities, operating model, and risk posture.

• Chairs or co-leads executive architecture and AI governance forums (e.g., AI Architecture Review Board), establishing decision rights, design authorities, exception processes, and enterprise adoption guardrails.

• Directs the enterprise “intelligence layer” strategy, defining reference architectures, standards, reusable patterns, and platform capabilities that enable consistent, scalable AI adoption across the enterprise.

• Defines and governs the enterprise agentic AI strategy and platform blueprint, including design, deployment, and lifecycle management of autonomous and semi-autonomous agents using platforms such as AWS Agent Core and Azure AI Agent Service.

• Establishes enterprise patterns for multi-agent orchestration, reasoning, tool-use, memory, human-in-the-loop controls, observability, fail-safes, and model/agent lifecycle management, ensuring scalable and auditable decision workflows.

• Sets enterprise standards for GenAI and agentic solutions across AWS and Azure, ensuring reliability, resilience, performance, security, cost optimization, and regulatory compliance.

• Owns the enterprise Retrieval-Augmented Generation (RAG) strategy and common frameworks, defining best practices for retrieval strategies, embeddings, vector stores, context management, evaluation, and performance tuning.

• Establishes enterprise standards for knowledge governance, including content provenance, permissions and access models, lineage, data quality, and safe/approved knowledge sources.

• Defines enterprise integration patterns that enable AI solutions to interface with legacy platforms (e.g., mainframes,…