Engineering Senior Manager - AI Enablement

The Head of AI Enablement is accountable for establishing and operating the enterprise capabilities required to enable safe, scalable, and measurable adoption of AI across the organization. The role leads enablement for AI platforms, tooling, implementation support, governance execution, and adoption practices so that AI capabilities are institutionalized, repeatable, and durable—not dependent on one-off delivery or individual heroics. 

This leader manages the activities and strategic direction of the AI Enablement function, including a blended team of engineers and contractors supporting implementation, governance coordination, and specialized AI-related work. The role is responsible for translating AI strategy into practical execution, driving cross-functional adoption, and ensuring AI enablement capabilities are scalable, controlled, and aligned to enterprise technology, risk, and regulatory expectations. The Head of AI Enablement serves as a primary contact to divisional peers, Technology leadership, risk and control partners, and business stakeholders, and oversees team development, execution management, and vendor coordination. 

Primary Responsibilities 

Enterprise AI Enablement Capabilities 

• Define and operationalize the enterprise AI enablement model, including onboarding, implementation guidance, reusable patterns, support processes, and scaling mechanisms for development teams and business technology partners. 

• Lead execution of AI platform enablement across the organization, ensuring teams have practical pathways to adopt approved AI capabilities in a controlled, supportable, and measurable manner.  

• Establish and maintain reusable implementation patterns, technical guardrails, reference architectures, and self-service materials that support adoption of approved AI capabilities across products, workflows, and engineering processes.  

• Drive operational enablement for strategic AI initiatives, including coordination of platform readiness, implementation support, and adoption execution for priority enterprise efforts.  

• Own the enablement of AI-related tooling and supporting processes so teams can independently and consistently apply approved capabilities while adhering to enterprise standards. [2026Feb_Jo...ty_Lead_v2 | Word] 

• Partner with governance, risk, security, architecture, and technology control stakeholders to ensure AI enablement is aligned to enterprise policies, approval requirements, control expectations, and evidence needs. [2026Feb_Jo...ty_Lead_v2 | Word] 

• Coordinate governance execution as it relates to AI implementation, including intake support, implementation standards, traceability, and readiness expectations for adopting teams.  

• Provide oversight for specialized AI-related workstreams, including contractor-supported implementation efforts and focused technical initiatives requiring accelerated delivery or subject matter expertise.  

• Build durable adoption mechanisms beyond training, including office hours, implementation playbooks, templates, reusable examples, FAQs, and measurable enablement practices.  

• Track adoption, implementation progress, execution risks, dependencies, and impediments across the enablement portfolio; escalate issues early and drive actions to closure.  

• Support enterprise AI use-case delivery by helping teams move from concept to controlled execution, with clear expectations regarding platform u