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VP, AI - First IT and Transformation

Remote / Online - Candidates ideally in
Des Moines, Polk County, Iowa, 50319, USA
Listing for: The Mutual Group
Remote/Work from Home position
Listed on 2026-05-20
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Description

As the Vice President, AI-First IT and Transformation, you will play a key role in supporting The Mutual Group (TMG), Guide One Insurance, and future members by establishing and scaling TMG’s enterprise AI capability, helping the organization apply AI in practical, secure, and measurable ways across business processes, technology platforms, IT delivery, operations, and employee productivity.

Department

Information Technology

Work Arrangement
  • Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in‑office schedule. The initial training period may require additional in‑office days.
Enterprise AI Strategy & Transformation Leadership
  • Define and lead TMG’s enterprise AI strategy in partnership with the CITO, business executives, technology leaders, and risk governance partners.
  • Establish the AI-First IT operating model, roadmap, governance approach, funding priorities, delivery rhythm, and measurable outcomes.
  • Build a disciplined portfolio of AI initiatives that balances experimentation, speed, security, business value, operational readiness, and risk management.
  • Translate emerging AI capabilities into practical, secure, scalable solutions that improve business outcomes, employee productivity, and technology delivery.
  • Serve as a thought leader and practical operator who helps the organization understand where AI can create value, where it creates risk, and how to adopt it responsibly.
AI Platforms, Architecture & Engineering Enablement
  • Lead the strategy and delivery of foundational AI platform capabilities that support secure, scalable, and reusable AI-enabled applications.
  • Define architecture patterns for AI-First applications, copilots, intelligent workflows, automation agents, enterprise knowledge solutions, and reusable AI components.
  • Guide platform capabilities such as model access, retrieval frameworks, vector databases, enterprise knowledge integration, prompt and response controls, observability, and governance guardrails.
  • Introduce AI-assisted software engineering practices across the SDLC, including coding, testing, documentation, requirements analysis, code review, and engineering workflow automation.
  • Partner with Applications, Engineering, Infrastructure, Operations, Architecture, Security, and Data teams to pilot, refine, and scale AI-enabled practices over time.
Business Capability Enablement & Adoption
  • Partner with underwriting, claims, operations, finance, customer service, and other business functions to identify and deliver high-value AI-enabled process improvements.
  • Lead the development of AI capabilities such as decision support, workflow automation, document intelligence, knowledge assistance, summarization, triage, productivity tools, and service quality improvements.
  • Help business teams move from AI ideas to practical use cases with clear outcomes, adoption plans, controls, and value measures.
  • Lead enterprise enablement of AI productivity tools such as ChatGPT, Microsoft Copilot, and related assistants, including standards, training, adoption practices, and usage guardrails.
  • Build reusable playbooks, enablement models, and communities of practice that raise AI fluency across IT and the broader organization.
Responsible AI, Governance & Risk Partnership
  • Work closely with the Senior Director, AI & Technology Risk Governance to ensure AI adoption is responsible, secure, compliant, and aligned with TMG’s risk appetite.
  • Embed security, privacy, responsible AI, sensitive data handling, human oversight, vendor risk, and production readiness into AI platforms, business use cases, engineering practices, operations, and employee tools.
  • Partner with Security, Legal, Risk, Compliance, Data, Architecture, and business teams to define and operationalize enterprise AI governance.
  • Create governance models that support responsible experimentation while protecting customers, employees, business partners, and enterprise data.
Team Leadership, Delivery & Enterprise Collaboration
  • Build and lead a small, high‑performing AI-First IT organization with strong architecture, engineering, automation, platform, and delivery capabilities.
  • Lead from the front with a hands‑on,…
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