AI Program Manager

Art and Wellness Enterprises•Bentonville, AR

23h•Onsite

About The Position

The AI Program Manager is a strategic thought leader that designs and operationalizes an enterprise AI ecosystem across Art and Wellness Enterprises (AWE) and the diverse, complex portfolio of supported organizations spanning healthcare, arts, education, and philanthropy. This role moves beyond isolated AI tools and instead establishes a governed, scalable, and version-controlled AI architecture that enables repeatable, auditable, and value-driven outcomes, with a focus on automation and responsible AI usage. This role defines and implements the foundational architecture, governance model, and versioning strategy required to support AI-enabled workflows and automation across the organization. This includes designing system-level prompts, decision frameworks, and behavioral rules that ensure consistency, traceability, and compliance across all AI agents and solutions. This role owns the development of the architecture and strategy, as well as the hands-on execution of AI-enabled workflows and automation. The AI Program Manager partners closely with executive leadership, technology teams, and business units to ensure AI is deployed as an integrated ecosystem—grounded in governance, structured architecture, and measurable business value—not as bespoke, one-off solutions. This role is also responsible for accelerating adoption of AI-enabled ways of working by partnering cross functionally to understand opportunities, strategies, and building repeatable AI driven solutions. Success in this role requires strategic thinking, strong relationship-building and communication skills, and the ability to influence stakeholders across technical and operational teams. The ability to balance enterprise AI strategy, governance, and architecture with practical execution, organizational change, and responsible AI adoption is essential, along with the ability to navigate ambiguity, build consensus, and deliver measurable organizational value in a fast-paced, evolving environment.

Requirements

Bachelor’s degree in statistics, economics, analytics, mathematics, computer science, information technology, or a related field required; Master’s degree preferred.
7–9+ years of progressively responsible experience in enterprise transformation, technology strategy, governance, or architecture roles, including meaningful experience in client-facing roles.
Demonstrated experience designing scalable systems, frameworks, and operating models.
Experience defining governance frameworks, controls, and policy structures.
Experience working in regulated, compliance-driven, or audit-sensitive environments is strongly preferred.
Proven success working alongside technical, product, data, or engineering teams to position and operationalize technology-enabled transformation programs.
Strong understanding of AI/automation use cases and enterprise deployment challenges.
Demonstrated decision-making skills and expertise in change management and adoption in complex organizations.
Excellent executive communication, facilitation, and stakeholder management skills, with the ability to translate complex concepts into clear, actionable organizational insights and business value.
Proven ability to operate effectively in ambiguous, fast-moving environments and to connect strategy, solutioning, and organizational execution.
Demonstrated analytical and problem-solving skills with the ability to identify challenges, evaluate options, and implement practical solutions.
High level of professional integrity and the ability to handle sensitive issues and situations with discretion.
Ability to work both independently and collaboratively within a multidisciplinary team.
Demonstrated ability to remain focused and steady in fast-paced environments with competing demands, including periods of transition, uncertainty or operational strain.
Ability to thrive in a fast-paced, ever-changing environment, remaining adaptable and resilient.

Responsibilities

Define and implement a scalable AI architecture and framework capable of supporting multiple agents, workflows, and business use cases across the AWE ecosystem.
Establish design principles for role-based agents, scoped tool usage, and modular AI components.
Develop and maintain reusable patterns for AI-enabled workflows (e.g., financial review, operational analysis, stakeholder reporting).
Design system prompts, reasoning frameworks, and rule sets that define how AI agents interpret data and generate outputs.
Standardize prompt structures to ensure consistency across use cases and teams.
Establish meta-rules governing agent behavior (e.g., prioritization logic, discrepancy handling, data validation standards).
Continuously refine prompts and rule sets as part of a controlled, versioned improvement process.
Design and implement a formal AI governance framework aligned with organizational risk management and compliance requirements.
Establish policies for responsible AI use, data integrity, model behavior, and decision transparency.
Define control mechanisms to ensure AI outputs can be reviewed, validated, explained, and audited.
Partner with leadership to position AI governance as a core capability, similar to financial and operational controls.
Develop and enforce versioning standards across all layers of the AI ecosystem, including prompts, business logic, data schemas, and outputs.
Maintain a structured version control system enabling rollback, comparison, and audit of AI-driven outputs.
Ensure that every AI-generated outcome can be traced back to its underlying logic, assumptions, and versioned configuration.
Create documentation standards that capture decision logic and evolution over time.
Design and implement a structured change management approach to support adoption of AI-driven workflows and operating model changes.
Guide business units in transitioning from manual processes to AI-supported decision-making frameworks.
Develop adoption roadmaps, readiness assessments, stakeholder engagement strategies, communications, and value realization frameworks tailored to AI-enabled transformation.
Partner with leaders and team members to identify, anticipate, and address barriers to AI adoption, including trust, capability gaps, process and operating model changes, and responsible AI considerations.
Develop and implement practical change interventions that accelerate AI adoption and sustain organizational change beyond initial deployment.
Support the development and implementation of training, communications, and stakeholder engagement strategies that accelerate adoption and sustain long-term organizational change.
Partner with technology teams to ensure architecture and governance are embedded into all technical implementations.
Collaborate with business leaders to identify, prioritize, and develop high-value AI use cases suitable for scalable AI deployment, building and maintaining an enterprise roadmap and prioritization for future development.
Ensure all AI solutions align with enterprise architecture standards rather than isolated experimentation.
Serve as the integration layer between technical development and operational execution, ensuring AI solutions are practical, scalable, and aligned with organizational objectives.
Advise executive leadership and stakeholders on AI strategy, governance, organizational readiness, and opportunities to improve operational effectiveness through AI-enabled solutions.
Represent the organization’s AI transformation capabilities internally and externally through presentations, industry forums, and thought leadership opportunities.
Stay current on emerging AI technologies, enterprise adoption patterns, governance practices, workforce implications, and change management practices relevant to enterprise transformation.
Help shape the organization's narrative around responsible, practical, and value-oriented AI adoption.
Perform other duties and responsibilities as assigned to support evolving organizational needs.