Director, AI Enablement

Zebra Technologies•Holtsville, NY

1d•$177,920 - $266,880•Hybrid

About The Position

The Director, AI Enablement is responsible for enabling consistent, scalable, and responsible internal AI adoption across Product & Solutions (P&S). This role establishes the operating model, alignment mechanisms, and practical guardrails that allow P&S organizations to independently drive AI enabled improvements while ensuring those efforts align with enterprise requirements and P&S priorities. The role requires deep understanding of product development and delivery lifecycles and the ability to actively engage with execution teams to shape how AI is applied, measured and scaled.

Requirements

Bachelor’s degree in Engineering, Computer Science, Data Science, or a highly quantitative related field.
Minimum 10+ years of progressive leadership experience in product development, digital transformation, data science/analytics or related domains with significant exposure to AI enabled initiatives
Minimum of 5+ years’ operating as part of a product development team.
Must have experience delivering transformation initiatives spanning multiple business units or global geographies, supported by verifiable metrics, such as number users impacted, and percent efficiency gains.
Must have direct people management experience leading and developing data analytics, business intelligence (BI), engineering, data science, or technical program/product management teams.

Nice To Haves

Master’s degree (MBA or equivalent).
Leadership of at least one significant cross-functional GenAI or automation initiative focused on modernizing operational workflows.
Deep understanding of product development and delivery lifecycles, with the ability to engage credibly with Engineering, Product, and PMO leaders.
Proven ability to translate cross functional initiatives into measurable business impact and productivity improvements.
Strong understanding of data architecture principles and what constitutes “AI data readiness” at enterprise scale.
Strong track record of influencing outcomes and driving alignment without direct authority.
Demonstrated experience communicating complex topics clearly and effectively to executive-level audiences.
Strong understanding of modern machine learning techniques and large language models, with the ability to guide decision making across data, modeling, engineering, and cloud platform teams.
Familiarity with enterprise governance, risk, security, or regulatory environments.

Responsibilities

Establish and maintain a clear, repeatable operating model for internal AI adoption across P&S, ensuring AI initiatives consistently address workflow design, risk considerations, reuse opportunities, adoption planning, and outcome measurement.
Provide portfolio level visibility into AI initiatives across P&S, actively engaging with execution teams to identify duplication, conflicting approaches, and opportunities to scale effective solutions.
Maintain a reuse register capturing AI patterns, workflows, agents, vendors, and lessons learned, and actively guide teams toward reuse where it improves scale, cost, or consistency.
Translate enterprise AI governance, security, legal, and regulatory requirements into practical, actionable expectations for P&S teams, working directly with execution leaders to integrate requirements into existing workflows.
Serve as an active thought partner to PMO, Engineering, and Product leaders, helping teams reason through how AI should be applied, where it adds value, and how success should be measured in the context of their workflows.
Establish a common measurement framework for AI adoption across P&S and work with execution teams and analytics partners to enable consistent visibility into adoption, productivity, and business outcomes using team-defined metrics.
Lead and develop an internal business intelligence team, guiding their evolution toward predictive analytics and foundational data readiness to support the broader AI operating model
Capture successful AI practices emerging from execution teams and enable reuse through shared guidance, reference examples, and cross-team knowledge sharing.
Drive alignment and outcomes across P&S through influence, partnership, and guidance, enabling teams to independently execute AI-enabled improvements within shared standards.
Act as a trusted advisor to P&S leadership by synthesizing AI adoption trends, outcomes, and maturity to support executive decision-making and cross-functional alignment.
Identify and escalate alignment issues, at both the team and organizational level, that create material risk, cost, or scalability concerns for AI adoption across P&S.