AI Tooling Strategy & Lifecycle Management Director

AI Tooling And Lifecycle Director

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

The AI Tooling and Lifecycle Director owns the strategy, governance, roadmap, lifecycle, standards, and enterprise coordination model for Vizient's AI tooling ecosystem. This role is responsible for establishing a scalable, secure, cost-effective, and governed AI tooling framework that enables Vizient's AI-First Development Lifecycle across AI Engineering, AI Quality Engineering, LLMOps/AIOps, Product, Governance, and Delivery teams.

The Director maintains an enterprise-wide view of AI tools, capabilities, ownership, licensing, integrations, costs, risks, and operational health while driving tool evaluation, vendor management, implementation readiness, adoption, optimization, renewal, and retirement. This leader partners across Technology, Security, Architecture, Procurement, Finance, Legal, and Product organizations to ensure AI platforms and tooling effectively support enterprise objectives.

Responsibilities

AI Tooling Strategy & Roadmap

• Develop and maintain Vizient's enterprise AI tooling strategy and roadmap aligned with the AI Development Lifecycle (AI-DLC), enterprise architecture, security, governance, product, and delivery priorities.
• Identify tooling gaps, duplication, interoperability challenges, adoption barriers, operational risks, and consolidation opportunities across the AI ecosystem.
• Recommend tooling investments, lifecycle decisions, optimization strategies, and rationalization opportunities to executive leadership.
• Establish long-term plans that support scalable AI platform growth and enterprise engineering productivity.

AI Tool Lifecycle Management & Standards

• Own the enterprise lifecycle framework for AI tooling, including evaluation, onboarding, implementation, adoption, optimization, renewal, and retirement.
• Establish standards for AI tool intake, ownership, access management, onboarding, integration readiness, documentation, observability, operational support, lifecycle reviews, and retirement.
• Maintain a comprehensive enterprise inventory of AI tools, capabilities, owners, users, licenses, integrations, vendors, costs, risks, controls, and operational status.
• Ensure tooling governance aligns with enterprise security, compliance, and Responsible AI standards.

Governance, Vendor Management & Enterprise Enablement

• Partner with Architecture, Security, Infrastructure, Governance, Compliance, Procurement, Legal, Finance, Product, Engineering, Platform, and LLMOps/AIOps teams to align AI tooling with enterprise standards and business objectives.
• Coordinate vendor engagement and platform partnerships, including vendor evaluations, support models, escalation processes, roadmap planning, contract renewals, and performance management.
• Monitor AI tooling spend, license utilization, adoption trends, renewal schedules, operational risks, and cost optimization opportunities.
• Facilitate enterprise intake, prioritization, and cross-functional review of AI tooling requests, implementation dependencies, lifecycle decisions, and operational readiness activities.
• Serve as the central coordination point for enterprise AI tooling governance and lifecycle management.

Qualifications

• Bachelor's degree or equivalent combination of education and relevant experience preferred.
• Minimum of seven (7) years of progressive experience in technology, platform engineering, enterprise tooling, AI platforms, Dev Ops, engineering enablement, or related disciplines.
• Demonstrated ability to lead cross-functional initiatives involving technology strategy, governance, platform operations, vendor management, and enterprise stakeholder engagement.
• Strong analytical, organizational, communication, and relationship management skills with the ability to influence across technical and business organizations.
• Experience operating as a hands-on player-coach in a lean, fast-paced, evolving enterprise environment.
• Experience with in healthcare, payer, provider, clinical, life sciences, or other highly regulated industries.
• Experience administering, configuring, or integrating enterprise engineering, Dev Ops, cloud, data, observability, governance, or productivity platforms.
• Experience with platforms such as Git Hub Enterprise, Azure Dev Ops, Service Now, Databricks, Microsoft Entra , model-provider platforms, or similar enterprise technologies.
• Experience supporting AI delivery platforms, LLMOps, AIOps, AI Quality Engineering, prompt management, agentic AI tooling, model evaluation, or Responsible AI governance.
• Experience with Internal Developer Platforms (IDPs), developer portals, platform…