AI Program Specialist

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The AI Program Specialist is responsible for orchestrating the intake, prioritization, and delivery of AI initiatives across the enterprise through a structured AI execution and governance model. This role ensures alignment of the AI initiative portfolio and product roadmaps with business objectives and compliance with regulatory, security, and data governance requirements. Acting as a communication bridge between business and technical teams, the AI Program Specialist leads AI demand intake, defines AI problem statements and charters, and translates business needs into executable AI product and project requirements, while articulating AI outcomes in clear, actionable terms. The role provides hands-on program and product management oversight for AI initiatives, manages cross functional workflows, and ensures adherence to governance, testing, and deployment standards. Additionally, the role drives responsible and scalable AI adoption by embedding continuous improvement practices, standardized delivery playbooks, and operational readiness, ensuring all AI solutions meet fairness, privacy, and security expectations before deployment.

Key Responsibilities

• Champions a corporate culture that emphasizes transparency, integrity, safety, environmental responsibility, employee development, diversity and inclusion, customer service, and operational excellence.
• Own and maintain an enterprise AI roadmap and intake backlog that aligns with organizational strategic goals and communicates priorities effectively to stakeholders and vendors.
• Plan, govern, and execute AI initiatives as products and programs, ensuring AI capabilities are implemented across different products with consistent user experiences.
• Bridge experimentation and production by operationalizing AI use cases, ensuring technology solves real-world business problems.
• Manage the end-to-end lifecycle of AI initiatives, guaranteeing post-launch value generation, collecting feedback, and evolving products for continuous impact.
• Lead AI value discovery, justification, and prioritization, articulating business pain points, justifying AI solutions' business value, and managing product backlogs to focus on high-value initiatives.
• Define AI charters, product specifications, epics, user stories, and acceptance criteria, independently and in collaboration with engineering, design, and documentation teams.
• Embed governance-by-design by engaging with compliance and legal teams throughout the product lifecycle.
• Serve as a visible advocate for AI-enabled continuous improvement, leveraging examples from within the organization and other industries to secure buy-in and funding for data-driven initiatives.
• Enable organizational readiness for AI adoption, by contributing to the design and delivery of targeted training programs, awareness campaigns, and narratives that encourage responsible AI and data use.
• Partner with QA, MLOps, SRE, and platform teams to implement product release cycles and ensure operational quality standards before deployment.
• Establish and continuously improve AI intake, prioritization, and execution frameworks, enabling transparent decision-making, standardized charters, and portfolio-level visibility across all AI initiatives.

Qualifications

Required Education, Skills & Experience

• A bachelor's degree in business, engineering, computer science, data science, AI, or a related field (advanced degree preferred)
• At least four years of experience managing AI, data, or advanced analytics initiatives in a product, program, or delivery is required
• Demonstrated experience delivering AI-enabled products, platforms, or services including machine learning, and generative AI from concept to production.
• Strong experience in product management, program management, or AI portfolio management is highly preferred
• Exposure to cloud infrastructure, MLOps practices, and agile or hybrid delivery methodologies is preferred.
• Working understanding of organizational infrastructure, networking and security concerns in on-premises and cloud environments
• Familiarity with AI lifecycle processes including data acquisition, model development, validation, deployment, monitoring, and performance management.
• Ability to deliver incremental value and measurable outcomes across each stage of the AI product and project life cycle
• Ability to understand and manage interdependencies between data, technology platforms, business processes, and user workflows
• Excellent product management skills and experience using agile approaches; ability to prioritize tasks and manage cross-functional teams
• Strong business acumen including the ability to assess financial impact, operational value, risk, and strategic alignment of AI initiatives
• This level is based only on availability in approved org design/structure;strict adherence is required
• Progression to this level is strictly restricted on the basis of critical individual capabilities and business requirements; must be supported by market survey data

Key Competencies

BEHAVIORAL

• Building Partnerships
• Leading Teams
• Business Acumen
• Communication
• Courage
• Building Self-Insight
• Driving for Results
• Energizing the Organization
• Driving Execution
• Building Trusting Relationships
• Driving Innovation
• Planning and Organizing
• Safety
• Establishing Strategic Direction

TECHNICAL

• Analytical skills
• Compliance
• Operations Resource Management
• Operations Risk Management
• Technology Integration
• Data and analytics fluency
• AI/ML lifecycle knowledge

May perform other duties as assigned.

Salary dependent on experience, skills, education, and training.