Bachelor's degree in relevant field or equivalent experience.
10 years of leadership experience in IT, data, analytics, or AI/Automation.
Experience with data governance and model risk management programs.
Proven leadership in software development and AI/ML in an enterprise context.
Strong understanding of data management and lifecycle controls.
Ability to translate regulatory and risk requirements into practice.
Strong communication and stakeholder management skills.
Responsibilities
Lead AI/Automation development and delivery teams.
Set strategic direction and priorities for AI initiatives.
Ensure adherence to governance and operational standards.
Coach and develop technical teams for high performance.
Drive cross-functional collaboration for faster delivery.
Manage vendor relationships for AI and automation capabilities.
Develop and implement a framework for AI/Automation governance.
Benefits
Hybrid work model allowing flexibility.
Opportunities for professional development and coaching.
Engagement in high-impact, cutting-edge technology initiatives.
Collaborative work environment with cross-functional teams.
Involvement in shaping enterprise-level governance practices.
Full Job Description
Lead and manage AI/Automation development, machine learning, data engineering, and automation delivery teams.
Set strategic direction, delivery priorities, architecture guardrails, and development standards for AI and automation initiatives.
Oversee solution planning, resource allocation, delivery execution, and operational readiness for AI and automation products and services.
Ensure development teams follow approved governance, security, testing, documentation, and release management practices.
Coach and develop managers, engineers, data scientists, and technical leads to build a high-performing, accountable, and innovative organization.
Drive collaboration across product, infrastructure, security, analytics, and business teams to accelerate value delivery and adoption.
Manage vendor and partner relationships supporting AI, data, and automation capabilities.
Support budget planning, investment prioritization, and workforce planning for governance and delivery functions.
Develop and lead the enterprise framework for AI/Automation governance, data governance, and responsible automation practices.
Establish policies, standards, and controls for data quality, metadata, lineage, model governance, risk management, security, privacy, and compliance.
Define governance processes across the AI and data lifecycle, including intake, approval, development, testing, deployment, monitoring, and retirement.
Partner with business, legal, compliance, security, privacy, and technology leaders to align governance with organizational risk appetite and strategic priorities.
Oversee governance for AI/Automation use cases, models, and automation solutions to ensure transparency, accountability, explainability, and auditability where appropriate.
Lead governance forums, review boards, and decision-making processes for AI, data, and automation initiatives.
Develop metrics, dashboards, and reporting to measure governance maturity, control effectiveness, adoption, and business value.
Monitor evolving regulatory, ethical, and industry requirements related to AI, data, and automation and translate them into actionable enterprise policies.
Performs all other miscellaneous responsibilities and duties as assigned or directed.
#LI-Hybrid
Bachelor's degree in Information Technology, Computer Science, Data Science, Engineering, or equivalent combination of education and experience.
Ten years of progressive leadership experience in IT, data, analytics, AI/Automation, or digital technology functions.
Experience establishing or leading data governance, AI/Automation governance, model risk management, or technology governance programs.
Experience leading software development, AI/ML, data engineering, or automation teams in an enterprise environment.
Strong knowledge of data management practices including data quality, metadata, lineage, stewardship, master data, and information lifecycle controls.
Strong understanding of AI and automation concepts, including model lifecycle management, responsible AI principles, process automation, and operational controls.
Demonstrated ability to translate technical, regulatory, and risk requirements into practical operating models, standards, and execution plans.
Experience working across legal, compliance, audit, security, privacy, and business functions in highly regulated or risk-sensitive environments.
Strong communication, executive presentation, stakeholder management, and organizational leadership skills.
Intermediate knowledge of Microsoft Office applications, including but not limited to, Word, Excel, PowerPoint, and Outlook.
