Director, AI Enablement

Zebra Technologies•Holtsville, NY

1d•$177,920 - $266,880•Hybrid

About The Position

The Director, AI Enablement enables consistent, scalable, and responsible internal AI adoption across Zebra’s Product & Solutions (P&S) organization. The role establishes the operating model, alignment mechanisms, and practical guardrails that allow P&S teams to drive AI-enabled improvements independently while aligning with enterprise requirements and P&S priorities. It calls for a strong understanding of product development and delivery lifecycles and the ability to engage credibly with engineering and technical teams to evaluate approaches, challenge assumptions, and shape how AI is applied, measured, and scaled. The Director translates complex technical and operational topics into clear, data-driven recommendations for senior leaders and drives alignment across business units and functions. The position leads and develops an internal business intelligence team, supports shared AI adoption measurement and reuse, and advises P&S leadership on adoption trends, outcomes, and maturity. The role requires working at least three days per week in the Holtsville, New York office and two days remotely in the United States.

Requirements

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

Nice To Haves

Master’s degree, MBA, or equivalent.
Direct 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 and 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 enterprise-scale AI data readiness.
Strong track record of influencing outcomes and driving alignment without direct authority.
Ability to synthesize complex technical and operational topics into clear, concise recommendations for executive 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 repeatable operating model for internal AI adoption across P&S, including workflow design, risk considerations, reuse opportunities, adoption planning, and outcome measurement.
Provide portfolio-level visibility into P&S AI initiatives and engage execution teams to identify duplication, conflicting approaches, and opportunities to scale effective solutions.
Maintain a reuse register of AI patterns, workflows, agents, vendors, and lessons learned, and guide teams toward reuse when it improves scale, cost, or consistency.
Translate enterprise AI governance, security, legal, and regulatory requirements into practical expectations for P&S teams and help execution leaders integrate them into existing workflows.
Partner with PMO, Engineering, and Product leaders to evaluate approaches, challenge assumptions, and determine how AI should be applied, where it adds value, and how success should be measured.
Establish a common AI adoption measurement framework across P&S and work with execution teams and analytics partners to provide consistent visibility into adoption, productivity, and business outcomes.
Lead and develop an internal business intelligence team, guiding its evolution toward predictive analytics and improved data readiness to support the broader AI operating model.
Capture successful AI practices 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 execute AI-enabled improvements independently within shared standards.
Advise P&S leadership by synthesizing AI adoption trends, outcomes, and maturity to support executive decision-making and cross-functional alignment.
Identify and escalate team- and organization-level alignment issues that create material risk, cost, or scalability concerns for AI adoption across P&S.