Engineering Director - Head of AI Engineering

Overview

The Director of AI Engineering manages the activities and strategic direction of multiple departments, including indirectly managing diverse Engineering and Architecture teams and enterprise AI Engineering platform teams. This role is responsible for budgets across multiple cost centers spanning concurrent development streams and provides both long‑and short‑term strategic direction in partnership with Engineering, Architecture, and Technology senior management.

The Director serves as a primary contact to Divisional peers, Management Group members, Bank‑wide senior management, and business partners. As a technology leader and industry expert, this role focuses on establishing AI (including Generative AI) as a governed, scalable, and value‑driven enterprise capability embedded within modern software delivery.

This position leads the strategic direction, operating model, and execution of enterprise AI Engineering, GenAI platforms, and AI‑enabled SDLC capabilities. The role is accountable for defining and operationalizing an end‑to‑end AI operating model spanning platform engineering, governance, security, and delivery, enabling consistent enterprise adoption while meeting risk, compliance, and regulatory requirements.

• Build Technology divisional strategy across departments in partnership with peers and Technology senior management, positioning AI and GenAI as core enterprise engineering capabilities
• Define and execute enterprise AI strategy and adoption roadmaps aligned to business outcomes and measurable value realization
• Establish and operationalize an end‑to‑end AI operating model spanning platform engineering, delivery execution, governance, and risk
• Partner with senior leaders outside of Technology to build strong client relationships supporting delivery of complex technology initiatives, including AI‑enabled transformation
• Serve as a primary interface to Technology leadership, business partners, and risk stakeholders, ensuring alignment, performance, and organizational development across AI engineering and platform teams

• Lead enterprise AI platform capabilities including GenAI platforms, LLM integration patterns, model and tool onboarding, and AI‑enabled developer experience
• Drive automation‑first SDLC transformation by embedding AI into development, testing, security, quality, and delivery workflows
• Oversee standardization of repositories, CI/CD pipelines, and engineering tooling to enable scale, reuse, and consistent governance
• Ensure integration of AI capabilities across enterprise platforms and delivery pipelines in alignment with Divisional standards and long‑range plans
• Monitor industry trends and vendor offerings relevant to AI engineering and SDLC modernization and initiate change when appropriate

• Oversee systems development activities of assigned teams, including staff assignments and ensuring timely completion within budget
• Define and manage AI delivery roadmaps, adoption models, success metrics, dependencies, milestones, and KPI/OKR reporting
• Implement maturity‑based adoption models (e.g., sandbox, controlled pilot, production) to scale usage while maintaining appropriate guardrails
• Drive enterprise adoption, enablement, and change management to increase developer productivity and accelerate delivery outcomes

• Define and operationalize AI standards, policies, and guardrails that balance enablement with compliance through automated controls and documentation
• Partner with Risk, Security, and Compliance teams to embed controls and regulatory alignment into AI platforms, pipelines, and AI‑enabled SDLC workflows
• Maintain internal control standards, including timely implementation of internal and external audit requirements and remediation of regulatory findings
• Ensure adherence to the Company’s risk and regulatory standards in alignment with the Company’s Risk Appetite
• Design, implement, maintain, and enhance internal controls to mitigate risk and elevate…