Principal Architect - Gen AI
Job in
Nashville, Davidson County, Tennessee, 37230, USA
Listed on 2026-09-25
Listing for:
Sedgwick
Full Time
position Listed on 2026-09-25
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), AI Business & Operations
Job Description & How to Apply Below
R78346
By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.
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Principal Architect - Gen AI
** PRIMARY PURPOSE** **:
** 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.
** ESSENTIAL FUNCTIONS AND RESPONSIBILITIES*
* ** Enterprise AI Strategy, Governance & Executive Leadership*
* + 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.
** Agentic AI & Platform Architecture at Scale*
* + 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.
** Enterprise RAG, Knowledge Architecture & Reuse*
* + 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.
** Integration, Modernization & Cross-Platform Enablement*
* + Defines enterprise integration patterns that enable AI solutions to interface with legacy platforms (e.g., mainframes, SQL Server, on-prem systems) and modern cloud services, balancing modernization with resiliency and minimizing operational disruption.
+ Partners with Enterprise Architecture, Infrastructure, and Platform teams to ensure the AI ecosystem is embedded within enterprise identity, networking, monitoring, disaster recovery, and service management capabilities.
** Data, Ontologies, and AI-Ready Enterprise Foundations*
* + Partners with data, analytics, and platform teams leveraging technologies such as Palantir, Databricks, and Snowflake to define shared enterprise data architectures, ontologies, governance models, and operating practices that enable AI, agentic workflows, and advanced…
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