Director - AI Implementation Lead - COO Corporate Enablement Capabilities Team

Role Overview

The AI Implementation Lead is a role within the COO organization responsible for driving the adoption and practical application of AI capabilities across the Corporate Enablement Capabilities (CEC) function. This individual will leverage functional expertise and emerging AI capabilities to identify and prioritize opportunities, connect and scale proven AI solutions, promote AI adoption across the organization, and establish the governance and foundational capabilities required for sustainable execution.

The successful candidate will be accountable for the end-to-end lifecycle of AI initiatives, from opportunity identification and prioritization through implementation, adoption, and value realization. This role is pivotal in shaping the future of the CEC function by embedding intelligence, automation, and Responsible AI practices into core functional processes.

While this role will report to Citi’s Head of Procurement and Third-Party Management, a member of the CEC leadership team, and will work closely with all members of the CEC leadership with active engagement across CEC senior process leaders, senior AI stakeholders and technology partners.

Key Responsibilities

1. Leverage Functional Knowledge & Emerging External AI Capabilities

• Identify, assess, and prioritize AI opportunities across the functional organization
• Build understanding of functional processes, pain points, and emerging AI capabilities to connect business needs with practical solutions
• Parter with internal function heads to establish ideation sessions and working forums to surface use cases and drive engagement
• Help refine and mature opportunities for evaluation, sponsorship, and execution

2. Connect & Scale Proven AI Solutions

• Identify common patterns of work across functional teams and opportunities to leverage existing enterprise AI capabilities and solutions
• Partner with peer AI Implementation Leads and enterprise teams to share successful use cases, best practices, and reusable approaches
• Drive adoption of proven AI solutions to accelerate value delivery, improve consistency, and reduce duplication of effort
• Support implementation efforts by leveraging central coordination teams to facilitate execution across functional teams

3. AI Adoption Leadership & Capability Building

• Engage with senior leadership driving AI adoption strategies, communications, demonstrations, workshops, office hours, and other engagement activities to increase awareness and adoption of AI capabilities
• Partner with CEC teams to establish and scale forums that encourage idea sharing, collaboration, and innovation
• Leverage central communication capabilities and VOE program to share success stories, lessons learned, and practical applications to help build momentum and confidence in AI adoption

4. Establish a Consistent AI Foundation

• Partner with enterprise governance, controls, and technology teams to promote consistent application of AI policies, standards, and frameworks
• Support adoption of Responsible AI practices, controls, standards, and data management requirements
• Help ensure AI initiatives are aligned with established governance processes and risk management expectations

Required Qualifications

Experience

• 10+ yearsof experience in a related field, with extensive experience in business and functional management within a large-scale, global organization
• Proven track record of leading complex, technology-oriented transformation and/or business re-engineering projects from conception to completion
• Demonstrated experience in driving significant change and process transformation initiatives, with measurable business impact
• Broad and comprehensive knowledge of banking operations, processes, and the associated regulatory landscape

Technical & Strategic Skills

• Strong, practical understanding of how to applyAI, machine learning, and advanced analytics to solve real-world business problems and drive tangible value
• Familiarity with modern AI/ML platforms, data architecture, and the lifecycle of developing and deploying intelligent systems
• Expertise in process analysis, performance metrics, and data-driven decision-making
• Ability to envision and articulate how technology and re-engineering can be combined to create significant, measurable improvements

Leadership & Soft Skills

• Exceptional ability to influence and engage in a consultative modewith senior stakeholders across business, operations, technology, and compliance
• Proven ability to define a strategic vision and lead a cross-functional team to…