Principal Architect – Gen AI

Sedgwick

. Own and set the enterprise Generative AI and Agentic AI architecture vision and multi-year roadmap .

Posted 9/21/2026full-timeRemote • Tennessee • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Generative AI and Agentic AI architecture, with a strong focus on governance, integration, and operationalization of AI solutions across enterprise environments. Proven ability to lead cross-functional teams and drive alignment with executive stakeholders while ensuring compliance and risk management.

Highest-signal resume keywords

Generative AI ArchitectureAgentic AI StrategyAWS AgentCore ExpertisePython ProgrammingAI Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Enterprise ArchitecturePlatform ArchitectureMachine LearningData ScienceSQLPySparkVector StoresAI/ML Lifecycle ManagementAdvanced AnalyticsIntegration Patterns

Soft Skills

LeadershipTeam CollaborationDecision-MakingInfluencing StakeholdersCoaching

Tools & Technologies

AWSAzureLangGraphCrewAIPineconeOpenSearchAzure AI SearchPalantir FoundryAI Agent ServiceEnterprise Intelligence Layer

Certifications & Qualifications

Master’s Degree in AIMaster’s Degree in Machine LearningMaster’s Degree in Computer ScienceMaster’s Degree in Engineering

Industry Keywords

AI GovernanceData QualityComplianceRisk ManagementTransformation Office

Tech Stack

Tools & technologies

AWSAzureCloudPySparkPythonSQL

About the role

Key responsibilities & impact

Own and set the enterprise Generative AI and Agentic AI architecture vision and multi-year roadmap
Chair or co-lead executive architecture and AI governance forums
Direct the enterprise intelligence layer strategy, including reference architectures, standards, reusable patterns, and platform capabilities
Define and govern the enterprise agentic AI strategy and platform blueprint
Establish enterprise patterns for multi-agent orchestration, reasoning, tool use, memory, human-in-the-loop controls, observability, fail-safes, and lifecycle management
Set enterprise standards for GenAI and agentic solutions across AWS and Azure
Own the enterprise Retrieval-Augmented Generation strategy and common frameworks
Establish standards for knowledge governance, provenance, permissions, lineage, data quality, and approved knowledge sources
Define integration patterns for legacy platforms and modern cloud services
Partner with Enterprise Architecture, Infrastructure, and Platform teams on identity, networking, monitoring, disaster recovery, and service management
Define shared enterprise data architectures, ontologies, governance models, and operating practices with data, analytics, and platform teams
Establish standards for AI-ready data products, metadata, semantic layers, and data quality thresholds
Serve as executive technical authority to security, risk, legal, compliance, and audit stakeholders
Establish practices for model governance, evaluation, red teaming, bias mitigation, explainability, and controls
Lead the enterprise AI architecture portfolio and prioritize capabilities and investments
Define success metrics and track value realization
Partner with Technology and Business leadership to transition AI initiatives into production operations
Build and develop enterprise AI architecture talent, coach senior architects, and create communities of practice
Influence platform/tooling decisions, vendor strategy, and ecosystem partnerships
Represent the organization as a senior AI architecture leader in executive engagements and transformation initiatives
Perform other duties as assigned
Travel as required

Requirements

What you’ll need

Master’s degree in AI, Machine Learning, Computer Science, Engineering, or a quantitative discipline from an accredited college or university preferred
10+ years of related, progressive experience in enterprise architecture, platform architecture, or large-scale solution architecture
7+ years leading delivery and/or architecture of enterprise-scale GenAI, RAG, and Agentic AI capabilities in complex corporate environments, or an equivalent combination of education and experience
Executive-level expertise with AWS AgentCore and Azure AI Agent Service
Mastery of agentic frameworks such as LangGraph and CrewAI
Experience establishing enterprise AI governance, driving cross-LOB adoption, and operationalizing AI solutions within security, risk, and compliance constraints
Ability to drive alignment and decision-making with executive stakeholders across Technology, Security, Risk, Legal/Compliance, and Lines of Business
Expert ability to bridge Data Science, AI Engineering, and Enterprise Architecture
Advanced mastery of Python, SQL, and PySpark
Deep expertise in vector stores such as Pinecone, OpenSearch, and Azure AI Search
Expertise in LLM platforms and AI/ML lifecycle management
Leadership in AWS and Azure enterprise environments
Functional exposure to advanced analytics platforms such as Palantir Foundry/AIP
Demonstrated success operating within a Transformation Office or enterprise innovation function
Ability to translate architecture decisions into measurable outcomes, cost efficiency, operational resilience, and risk reduction
Ability to work in a team environment
Ability to meet or exceed Performance Competencies

Benefits

Comp & perks

Work-life balance
Reasonable accommodations when applicable and appropriate
Equal Opportunity Employer
Drug-Free Workplace