Head of AI

The Head of AI is responsible for defining and delivering the bank’s enterprise-wide AI strategy across three core pillars:

• Workplace Productivity with Copilot
• Automation and Agentic AI
• AI Governance, Safety and Adoption Enablement

This role ensures AI is deployed responsibly, securely, and with measurable business value to provide strategic ownership of AI initiatives, unify technical and business direction, and oversee risk‑aligned AI implementation.

The Head of AI blends automation engineering, RPA/agentic orchestration, generative AI, and enterprise change leadership, steering the bank toward safe, scalable “AI‑native” operations. The role requires deep experience in automation tooling, workflow orchestration, RPA platforms, and emerging agentic AI capabilities.

• Strong grounding in data pipelines, model deployment, MLOps, CI/CD automation, and cloud‑based AI architectures
• Strong knowledge of AI safety, risk frameworks, responsible AI principles, and regulatory requirements (e.g., EU AI Act equivalents)
• Proven experience in AI, automation, or machine learning engineering leadership; strong working knowledge of RPA, agentic automation, workflow orchestration, and ML/LLM technologies
• Hands‑on experience designing and deploying automation solutions using tools such as UiPath, Blue Prism, Workato, Power Platform, or equivalent aligning with RPA/AI automation leader profiles
• Proven ability to develop and communicate AI strategy, influence senior stakeholders, and operate at C‑suite or executive levels
• Experience running or participating in AI governance bodies (AI councils, model oversight forums, risk committees)
• Experience embedding governance into development lifecycles, ensuring auditability, fairness, explainability, data protection, and secure usage
• Experience deploying large‑scale workplace technology (e.g., Copilot, M365, automation platforms) and ensuring organisational readiness, training, communications, and adoption tracking

Key Responsibilities

• Lead enterprise rollout of Microsoft 365 Copilot, ensuring adoption models reflect best practices for AI‑enhanced productivity, role‑specific training, safe usage guidelines, and incremental value realisation.
• Identify high‑impact workflow opportunities where Copilot can reduce cognitive load, accelerate document creation, improve analytics and decision support, and streamline communication across functions.
• Partner with Banking Value Streams to design ‘AI‑augmented roles’ and embed Copilot into daily workflows (meetings, analysis, customer service, operations).
• Build and scale an agentic / automation capability that blends RPA, workflow orchestration, generative AI agents, and API‑driven automation—reflecting industry guidance that financial services must converge AI and RPA to achieve end‑to‑end automation.
• Lead development of automated processes using RPA, intelligent document processing, conversational AI, and agentic orchestration frameworks.
• Establish automation opportunity pipelines, value cases, and engineering patterns that reduce cost, reduce cycle times, and improve operational resilience.
• Oversee technical design, architecture, and deployment of agentic workflows in partnership with Engineering, Data, InfoSec, and Operations teams.
• Define the bank’s AI vision, roadmap, capability model, and operating architecture—aligned with modern Head of AI responsibilities around strategy, R&D, and platform capability building.
• Translate strategy into measurable outcomes, KPIs, and investment cases including value delivery from Copilot, automation, agentic workflows, and risk‑controlled AI implementation.
• Evaluate, select, and govern enterprise AI tools, platforms, MLOps components, and automation technologies.
• Own enterprise AI governance, including model lifecycle oversight, safety guidelines, explainability, fairness, risk classification, and compliance with tightening AI regulations.
• Implement guardrails that ensure secure, responsible, and transparent usage of AI across the bank.
• Establish ethical standards and acceptable‑use boundaries in line with CTO responsibilities in governance, risk ownership, and executive accountability.
• Build and lead multi‑disciplinary teams across AI engineering, automation, RPA, experimentation, and change adoption, aligned with expectations for senior AI leaders.
• Work closely with Product, CTO, CRO, CPO, Real Estate Finance and Retail to integrate AI into core business operations.
• Communicate AI strategy and delivery outcomes to ExCo and Board; chair or participate in AI governance forums or AI councils.
• Lead prototyping of agentic AI capabilities, safe sandboxing, controlled pilots, and AI‑augmented workflows.
• Track industry developments in generative AI, copilots, LLMs, autonomous workflows, synthetic data, and control frameworks to maintain competitive advantage.
• Foster a culture of continuous experimentation and learning—mirroring the innovation expectations of modern AI leadership roles.

Hodge is an advocate of being an equal opportunities employer. We believe in promoting equality and diversity which is central to our lives today. We welcome applications from all sections of the community and recognise the value a diverse workforce brings to an organisation.

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