VP AI Engineering – Enterprise

Sedgwick

. Define and lead enterprise strategy for data and generative AI engineering .

Posted 10/6/2026full-timeRemote • Florida • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading enterprise strategy for data and generative AI engineering, with a strong focus on establishing standards, governance, and operational models for analytics and AI at scale. Proficient in managing AI platforms, financial oversight, and cross-functional collaboration to drive responsible adoption and measurable productivity improvements.

Highest-signal resume keywords

Data EngineeringGenerative AI EngineeringAI GovernanceSnowflake StrategyExecutive Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningFeature EngineeringAPIsWorkflow AutomationLLMsAgentic AIRAGEnterprise IntegrationData PermissionsFinancial Management

Soft Skills

LeadershipCommunicationCollaborationProblem-SolvingAdaptability

Tools & Technologies

SnowflakeAWSAzureChatGPT EnterpriseClaude

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree Preferred

Industry Keywords

Enterprise TechnologyData AnalyticsAI PlatformsSaaSCross-Functional Initiatives

Tech Stack

Tools & technologies

AWSAzureCloudETLSQL

About the role

Key responsibilities & impact

Define and lead enterprise strategy for data and generative AI engineering
Establish standards, roadmaps, and operating models for analytics, machine learning, and AI at scale
Oversee design, delivery, and operation of enterprise ETL/ELT platforms integrating mainframe, SQL Server, and DB2 with cloud data and AI platforms
Govern feature stores, analytically optimized datasets, and AI-ready data products
Set enterprise direction for vectorization, embeddings, retrieval-augmented generation, and secure data consumption
Own Snowflake strategy, including architecture, performance, cost governance, and AWS/Azure AI integration
Collaborate with Technology, Security, Infrastructure, Legal, Risk, and Compliance leaders
Establish operating metrics and financial discipline for data and AI engineering investments
Lead engineering leaders and teams, set priorities, remove barriers, and ensure execution
Advise executive leadership on data, AI, and generative AI capabilities, risks, and opportunities
Shape talent strategy, capability development, and succession planning
Lead AI engineering for HR, Marketing, Finance, Legal, and other corporate functions
Identify and deliver LLM, agentic AI, workflow automation, and knowledge-assistant use cases
Build reusable AI capabilities, agents, APIs, connectors, and workflow integrations
Administer and operate ChatGPT Enterprise and Claude
Manage users, licenses, roles, permissions, workspaces, and enterprise configurations
Establish approved connectors and integrations with enterprise data and applications
Define access controls, data-use guardrails, and standards for GPTs, agents, projects, and connectors
Monitor adoption, utilization, licenses, token/API usage, platform effectiveness, cost, risk, and business value
Manage AI platform spend, forecasting, chargeback/showback, license optimization, and vendor commitments
Own relationships with OpenAI, Anthropic, and other enterprise AI providers
Evaluate, pilot, restrict, or broadly adopt new platform capabilities
Lead a small engineering/platform team responsible for AI solutions, integrations, administration, and support
Partner with business leaders to drive responsible adoption and measurable productivity improvement
Perform other duties as assigned
Provide supervisory leadership, hire colleagues, and conduct performance discussions

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Engineering, Artificial Intelligence or a related field from an accredited college or university required
Master’s degree preferred
10+ years of engineering, platform, or enterprise technology experience
5+ years in technical leadership
Ten (10) years of progressive experience in data engineering, analytics platforms, or AI-related technologies, including senior leadership responsibility for enterprise-scale data or AI initiatives, or an equivalent combination of education and experience required
Strong hands-on understanding of LLMs, agentic AI, RAG, APIs, workflow automation, and enterprise integration
Experience building AI solutions for HR, Marketing, Finance, or Legal
Experience administering enterprise SaaS or AI platforms at significant organizational scale
Strong understanding of identity, SSO, RBAC, connectors, APIs, data permissions, and enterprise security
Strong AWS and/or Azure knowledge
Experience establishing AI governance, access controls, monitoring, and responsible-use standards
Strong financial management skills involving technology consumption, licenses, vendor spend, and forecasts
Experience with Snowflake and AWS/Azure ecosystems
Experience with machine learning, feature engineering, vector databases, and RAG-based architectures
Experience managing large, cross-functional initiatives with significant financial and organizational impact
Exceptional executive communication skills
Ability to lead through ambiguity, scale new capabilities, and drive enterprise change
Ability to meet or exceed Performance Competencies
Travel as required

Benefits

Comp & perks

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