About The Position

This role is responsible for leading and managing AI/Automation development, machine learning, data engineering, and automation delivery teams. The Director will set strategic direction, delivery priorities, architecture guardrails, and development standards for AI and automation initiatives. They will oversee solution planning, resource allocation, delivery execution, and operational readiness for AI and automation products and services, ensuring teams follow approved governance, security, testing, documentation, and release management practices. Additionally, the role involves coaching and developing managers and technical leads to build a high-performing organization, driving collaboration across various departments, managing vendor relationships, and supporting budget and workforce planning. A key aspect of this position is developing and leading the enterprise framework for AI/Automation governance, data governance, and responsible automation practices, establishing policies, standards, and controls for the entire AI and data lifecycle. The Director will 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 to ensure transparency and accountability, lead governance forums, and develop metrics to measure governance maturity and effectiveness. The role also requires monitoring evolving regulatory and ethical requirements and translating them into actionable enterprise policies.

Requirements

  • 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.

Responsibilities

  • 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.
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