Head of AI Engineering - Director

Who we are

United by a sense of purpose towards our customers – to be a trusted partner for the long-term – and our universal banking platform in EMEA, SMBC Group has an international growth agenda and award-winning products, meaning we provide exciting opportunities to work on a diverse range of projects and initiatives. We deliver a full suite of corporate finance products and solutions to our customers as well as investment banking and advisory services, and a range of innovative solutions in global capital markets. Read on to find out how you could enhance your skills and gain valuable experience, by joining us to support our clients transition to a sustainable future.

Role Summary

We are seeking a visionary and technically accomplished Head of AI Engineering (Director) to lead the development and deployment of advanced AI solutions across SMBC EMEA. This role will oversee a team of AI engineers, delivering secure, scalable, and production-grade AI systems that support strategic use cases in Capital Markets and Corporate Banking.

The successful candidate will work closely with the AI Innovation and Transformation teams to align on deliverables, priorities, and solution architecture. The role will also require close collaboration with Architecture & Engineering teams, wider IT functions, to ensure seamless integration, platform alignment, and compliance with enterprise standards.

This is a hands-on, delivery-focused position that blends engineering leadership with cross-functional collaboration, regulatory awareness, and a strong commitment to responsible AI development in a regulated financial environment.

• Leads the delivery of enterprise-grade AI systems across the EMEA region, including LLM services, agentic workflows, Retrieval-Augmented Generation (RAG) pipelines and AI-powered applications.
• Manages a growing team of AI engineers, with responsibility for hiring, mentoring, and performance management.
• Works closely with the Head of AI Innovation, Architecture & Engineering leadership, and wider IT teams to ensure AI solutions are integrated, scalable, and compliant.
• Operates with a high degree of autonomy, accountable for the technical execution of the bank’s AI roadmap.
• Represents AI Engineering in senior forums, architecture boards, and regulatory engagements.

Business Area

This role will sit within the Architecture & Engineering area of our Information Technology and Security Department.

Reporting to the EMEA Head of Architecture & Engineering, the role requires constant communication with business partners, engineering, infrastructure, security teams, external parties, intra-group outsourcing partners, global teams to deliver scalable, secure, and future-ready technology platforms.

Position Description

SMBC recognises the transformative potential of artificial intelligence in shaping the future of financial services. As the bank accelerates its AI strategy, it is expanding its technical capabilities by establishing a dedicated AI Engineering function to build and scale secure, production-grade AI systems.

The Head of AI Engineering will lead this newly formed function, playing a pivotal role in delivering the technical foundation for the bank’s AI programme. This includes overseeing the development of advanced AI solutions—such as LLM-powered services, agentic workflows, and AI-enhanced applications—while ensuring alignment with enterprise architecture, security, and regulatory standards.

This role is critical to the success of SMBC’s AI ambitions and will work closely with other IT functions and other senior stakeholders to ensure that engineering delivery supports the bank’s broader innovation goals.

Accountabilities & Responsibilities

• AI Engineering Leadership
• Cloud Platform & Infrastructure Oversight
• Security, Compliance & Risk Management
• Collaboration & Stakeholder Engagement
• Team Management & Capability Building
• Delivery Oversight & Reporting
• Risk & Issue Management

Experience and Skills

Knowledge & Experience:

• Extensive experience in software engineering, with proven experience in AI/ML engineering leadership roles.
• Proven track record of delivering secure, scalable AI systems in regulated environments, ideally within financial services.
• Deep expertise in building and deploying advanced AI solutions, including:
• Document intelligence and GenAI applications
• Strong hands-on experience with cloud-native AI development on Microsoft Azure and Google Cloud Platform (GCP), including services such as Azure OpenAI, Azure ML, Vertex AI, and Gemini.
• Demonstrated ability to lead cross-functional engineering teams across front-end and back-end disciplines.
• In-depth understanding of secure engineering practices, including encryption, access control, secure context injection, and audit logging.
• Familiarity with AI governance and regulatory frameworks such as the EU AI Act, FCA/PRA guidance, GDPR, ISO/IEC 42001, and NIST AI RMF.
• Experience working closely with cybersecurity, legal, and risk teams to ensure compliance and audit readiness.
• Strong background in MLOps and DevSecOps, including CI/CD pipelines, model monitoring, drift detection, and infrastructure-as-code.

Skills:

• Ability to lead complex AI engineering programmes, set technical direction, and drive delivery across multidisciplinary teams.
• Deep expertise in designing scalable, secure, and modular AI systems, including LLM services, agentic workflows, and RAG pipelines.
• Strong understanding of secure coding practices, encryption, access control, and auditability in AI systems.
• Excellent interpersonal and stakeholder engagement skills, with the ability to work across engineering, innovation, risk, and compliance teams.
• Strong analytical and troubleshooting skills, with the ability to resolve complex technical and delivery challenges.
• Proven ability to build, mentor, and scale high-performing engineering teams in fast-paced, regulated environments.

Education & Qualifications:

• Educated to degree level in Computer Science, Engineering, Mathematics, or a related technical discipline (or equivalent professional experience).
• Postgraduate qualifications (e.g., MSc, PhD) in AI, Machine Learning, or Data Science are advantageous.
• Relevant certifications in cloud platforms (e.g., Microsoft Azure, Google Cloud Platform) and AI/ML engineering (e.g., TensorFlow Developer, Azure AI Engineer Associate) are desirable.
• Demonstrated commitment to continuous learning in AI system architecture, secure engineering, and cloud-native development.

Knowledge & Experience:

• Extensive experience in software engineering, with proven experience in AI/ML engineering leadership roles.
• Proven track record of delivering secure, scalable AI systems in regulated environments, ideally within financial services.
• Deep expertise in building and deploying advanced AI solutions, including:
• Document intelligence and GenAI applications
• Strong hands-on experience with cloud-native AI development on Microsoft Azure and Google Cloud Platform (GCP), including services such as Azure OpenAI, Azure ML, Vertex AI, and Gemini.
• Demonstrated ability to lead cross-functional engineering teams across front-end and back-end disciplines.
• In-depth understanding of secure engineering practices, including encryption, access control, secure context injection, and audit logging.
• Familiarity with AI governance and regulatory frameworks such as the EU AI Act, FCA/PRA guidance, GDPR, ISO/IEC 42001, and NIST AI RMF.
• Experience working closely with cybersecurity, legal, and risk teams to ensure compliance and audit readiness.
• Strong background in MLOps and DevSecOps, including CI/CD pipelines, model monitoring, drift detection, and infrastructure-as-code.

Skills:

• Ability to lead complex AI engineering programmes, set technical direction, and drive delivery across multidisciplinary teams.
• Deep expertise in designing scalable, secure, and modular AI systems, including LLM services, agentic workflows, and RAG pipelines.
• Strong understanding of secure coding practices, encryption, access control, and auditability in AI systems.
• Excellent interpersonal and stakeholder engagement skills, with the ability to work across engineering, innovation, risk, and compliance teams.
• Strong analytical and troubleshooting skills, with the ability to resolve complex technical and delivery challenges.
• Proven ability to build, mentor, and scale high-performing engineering teams in fast-paced, regulated environments.

Education & Qualifications:

• Educated to degree level in Computer Science, Engineering, Mathematics, or a related technical discipline (or equivalent professional experience).
• Postgraduate qualifications (e.g., MSc, PhD) in AI, Machine Learning, or Data Science are advantageous.
• Relevant certifications in cloud platforms (e.g., Microsoft Azure, Google Cloud Platform) and AI/ML engineering (e.g., TensorFlow Developer, Azure AI Engineer Associate) are desirable.
• Demonstrated commitment to continuous learning in AI system architecture, secure engineering, and cloud-native development.

What we offer

For all the expertise and experience you bring to help us make a difference, it’s only sustainable if we support you to build your career and be your best self so we offer competitive company benefits, centred around promoting positive well-bring and work-life balance. We also believe in fostering a diverse and inclusive work environment, where all team members perspectives and contributions are valued. Initiatives in place which promote a diverse and inclusive culture and healthy work life balance include hybrid working, Sport & Social Clubs and Diversity and Inclusion networks.