Director, AI Enablement
$177,920–$266,880 year
On-siteHoltsville, New York, United States
Job Summary
Establish a repeatable operating model for internal AI adoption across Product & Solutions, defining workflow design, risk considerations, and outcome measurement frameworks. Provide portfolio-level visibility into AI initiatives by identifying duplication and scaling effective solutions while maintaining a reuse register of patterns, workflows, and lessons learned. Translate enterprise governance, security, and regulatory requirements into actionable expectations for execution teams, acting as a trusted advisor to PMO, Engineering, and Product leaders. Lead the evolution of an internal business intelligence team toward predictive analytics and guide cross-functional alignment through shared standards and knowledge sharing. Identify and escalate alignment issues that create material risk or scalability concerns for AI adoption.
Required Qualifications
- 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
Desired Qualifications
- 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
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