VP, IT Enterprise AI

Position Overview


The VP, Enterprise AI will define and deliver the organization's enterprise AI strategy, translating it into a governed, scalable, and measurable portfolio of AI capabilities and solutions. This role defines and implements the enterprise AI roadmap, establishes AI governance and responsible AI practices, leads AI program planning and execution, and serves as the owner of enterprise AI platform architecture as well as a thought partner to Business Sponsors and IT Application Owners for AI systems (build/buy/partner) across the enterprise.

The VP, Enterprise AI will partner closely with IT and Business Sr. Leadership, IT Security, ED&A, Legal, HR, Finance, Enterprise Architecture, and Product/Engineering leaders to ensure AI investments deliver measurable business value, reduce risk, and strengthen competitive advantage. The VP, Enterprise AI will provide both strategic oversight and tactical leadership to the business as they develop AI use cases and implement AI solutions.

The VP, Enterprise AI will develop AI education and end user support across the enterprise, serve as an AI advisor to executive leadership, develop and mentor direct and indirect reports, and foster a culture of pragmatic architecture and responsible innovation.

The role requires a strong blend of retail industry expertise, technical AI acumen, and ability to navigate from strategic vision to detailed execution to ensure the AI roadmap and programs remain aligned with the Company's strategic priorities, risk and compliance requirements, and financial plans.

A Day in the Life


Enterprise AI Strategy & Program Delivery

• Define and continuously evolve the enterprise AI strategy aligned to corporate goals, operating model, and investment priorities.
• Establish value hypotheses, measurable KPIs, and benefits tracking for AI initiatives.
• Create executive-facing narratives and decision materials for SLT/Board-level communication on AI strategy, progress, and risk posture.
• Maintain the multi-year AI Roadmap, including planning, budgeting, resourcing, and dependency management.
• Lead AI vendor strategy and partnerships (cloud providers, model providers, tooling vendors, systems integrators).
• Identify and prioritize AI opportunities across functions and provide oversight to AI portfolio financials, capacity planning, and benefits realization.

AI Governance and Risk Management

• Lead cross-functional Enterprise AI Governance board.
• Define and enforce policies for:
  Model risk management (bias, drift, explainability, monitoring);
  Data privacy/security requirements and information protection;
  Vendor/third-party AI risk and contract standards; AI usage standards for employees, including acceptable use, training, and auditability.
• Implement controls and processes for approvals, audits, incident response, and ongoing compliance with relevant regulatory and ethical expectations.
• Create intake, evaluation, stage gates, and release standards for AI initiatives-ensuring alignment with architecture, security, and value realization criteria.
• Drive program execution with clear milestones, risk management, and change management to ensure adoption and measurable outcomes.

AI Platform Architecture & Applications

• Develop enterprise AI platform blueprint and reference architecture spanning:
  Data pipelines, feature stores, and data governance integration;
  Model development, fine-tuning, evaluation, and lifecycle management; MLOps/LLMOps tooling, CI/CD, monitoring;
  Integration patterns.
• Partner with CISO to develop and maintain identity, access, and security controls (zero trust principles) and with Legal to embed controls and standard terms into vendor contracts.
• Align AI capabilities to target-state architecture and technology standards. Ensure scalability, reliability, and cost optimization across environments.
• Partner with ED&A leaders to ensure data readiness, quality, lineage, and governance enabling AI success.
• Serve as the technology owner for enterprise AI systems and services, including AI platforms, enterprise copilots and productivity AI, and domain AI products
• Define support and escalation paths with ITSM integration; ensure resilience, incident response, and continuity for AI services.

Adoption and End User Support

• Create a scalable enablement model (training, communities of practice, 3rd party resources).
• Develop change management strategies to drive adoption, shift ways of working, and ensure responsible use.

Leadership

• Oversee AI programs, projects, and activities, coordinating with IT Leadership.
• Implement performance metrics and executive-level reporting to support innovation and continuous improvement.
• Coach and mentor team members, fostering a culture of development and professional growth.
• Serve as an advisory and thought-partner to cross-functional executives and AI champions.

You'll Come With


Education and

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or Data Science.

Experience:

• 12+ years in technology leadership with 5+ years in AI/ML, data…