Applied AI ML Director

Join us to shape the future of AI and machine learning in financial services. You will lead innovative projects that deliver real business value, working closely with talented colleagues across Product, Engineering, Data, Risk, Compliance, and Operations. We offer opportunities for growth, hands-on technical challenges, and the chance to make a meaningful impact. Your leadership and expertise will help us deliver reliable, scalable solutions that transform how we serve our clients.

As an Applied AI ML Director in the International Consumer Bank (ICB) team, you will drive the end-to-end delivery of high-impact AI and machine learning solutions. You will partner with business leaders to define valuable use cases, translate outcomes into measurable objectives, and ensure production-ready deployments. Your role combines technical depth, people leadership, and strong delivery discipline. You will help shape our Applied AI/ML strategy and foster a culture of excellence and innovation.

• Own end-to-end AI delivery, partnering with the business to identify use cases and deliver production solutions
• Review and contribute to solution design, modelling, experimentation, and deployment architecture
• Unblock teams on complex technical issues with hands-on support
• Build, coach, and develop a high-performing team of data scientists, business analysts, and engineers
• Establish repeatable practices for data quality, evaluation, deployment, and monitoring
• Define and deliver the Applied AI/ML strategy for priority domains
• Create reusable patterns such as reference architectures, templates, and playbooks
• Partner with product, business leads, and the AI Delivery team to prioritize and deliver work
• Ensure solutions meet governance, privacy, and security requirements
• Present technical decisions and performance results to senior stakeholders
• Document assumptions, limitations, and controls

• Proven expertise and hands-on delivery of AI/ML in financial services
• Strong technical depth in GenAI/LLMs, prompt engineering, RAG architecture, fine-tuning, vector databases
• Knowledge of evaluation metrics for LLMs and safety/guardrail techniques
• Understanding of supervised learning and data engineering fundamentals
• Leadership experience with ability to build teams and lead cross-functional delivery
• Awareness of governance and controls in a regulated environment
• Excellent communication skills to distil complex technical topics for senior stakeholders

• Advanced degree in Computer Science, Engineering, Statistics, or a related field