AI lab manager

Sumitomo Mitsui Finance Dublin Limited is a wholly owned subsidiary of SMBC and is growing as a Centre of Excellence for the bank’s universal banking business across EMEA. It provides technology and operational support services aligned with SMBC’s growth, innovation, and transformation strategies.

• Manage the AI Lab’s ongoing operation, roadmap, service model, environments, access model, and user journey with an external vendor
• Define pathways for experimentation, proofs of concept, evaluation, and transition of viable solutions into the wider delivery factory
• Establish standards, templates, and controls for experimentation that meet security, data, architecture, AI governance, and third-party risk requirements
• Own the Lab roadmap, capacity, budget, service health, risks, dependencies, and management reporting
• Design and implement a transparent pipeline of AI opportunities from intake and triage through experiment design, execution, evaluation, and closure
• Define business problems, hypotheses, success measures, data needs, risks, and acceptance criteria with sponsors before work begins
• Oversee multiple experiments, maintaining momentum, ownership, timelines, decisions, and documented outcomes
• Facilitate evidence-based go, pivot, or stop decisions and distinguish experimentation from production delivery
• Package successful experiments, artefacts, and lessons learned for delivery teams
• Build relationships across business, technology, architecture, security, risk, data, and engineering teams to generate relevant use cases
• Promote the Lab through briefings, demonstrations, workshops, showcases, and success stories
• Chair planning and discovery sessions, translating business needs into technical conversations and experiment briefs
• Communicate technical concepts, constraints, and outcomes to technical and non-technical audiences
• Represent the Lab across the organisation and build consensus among stakeholder groups
• Own operational relationships with technology providers and coordinate delivery, support, roadmap alignment, and service performance
• Lead onboarding and collaboration with fintechs, AI providers, strategic vendors, and partners
• Align vendor expectations and delivery with internal architecture, security, procurement, legal, risk, and governance requirements
• Challenge technical options, integrations, delivery estimates, commercial dependencies, and platform capabilities
• Own the Lab as a product and prioritise investment and experiments by strategic relevance, business value, feasibility, risk, and delivery readiness
• Track utilisation, adoption, throughput, experiment outcomes, delivery conversion, benefits, cost, and stakeholder satisfaction
• Produce management reporting and use evidence to improve the Lab’s proposition, operating model, and platform utilisation
• Ensure experiments comply with information security, data protection, records management, model and AI governance, change, and audit requirements
• Promote responsible AI practices, including transparency, data minimisation, access control, output validation, and human oversight

• Substantial experience managing an innovation lab, technology platform, product, portfolio, or cross-functional innovation programme in a complex enterprise
• Proven programme and stakeholder management experience coordinating business sponsors, vendors, security, architecture, data, and engineering teams from concept through decision and hand-off
• Experience building demand, promoting a platform or service, running demonstrations and workshops, and developing a use-case pipeline
• Experience managing external technology partners and coordinating onboarding, collaboration, and delivery across multiple vendors
• Practical technical knowledge of cloud platforms, APIs, Git repositories, software delivery, solution architecture, and integrations
• Experience defining success measures, assessing experiment outcomes, and communicating the value delivered by an innovation platform or technology portfolio
• Proven delivery in a controlled enterprise environment, with understanding of security, data, resilience, third-party, change, and audit requirements
• Excellent communication and facilitation skills, including translating between business and technical audiences and building consensus across complex stakeholder groups
• Understanding of AI innovation platforms, digital sandboxes, or comparable experimentation environments
• Ability to oversee environments, user access, vendor workspaces, approved data, tooling, usage, and service performance
• Understanding of controls separating experimentation from production and transferring successful work into governed delivery
• Working knowledge of public cloud services, APIs, authentication, connectors, and enterprise integration patterns
• Familiarity with Git repositories, source control, software development lifecycles, testing, CI/CD, and environment promotion
• Ability to understand how code and APIs are used in solutions, interpret high-level architecture, and identify integration or delivery dependencies
• Comfortable discussing generative AI, retrieval, agents, data platforms, model services, observability, and human-in-the-loop controls without being the lead engineer
• Broad understanding of generative AI, machine learning, intelligent document processing, retrieval, and agentic AI use cases
• Ability to assess enterprise data, models, and external services against confidentiality, privacy, security classification, retention, and access requirements
• Understanding of responsible AI controls, including grounding, testing, transparency, output validation, human oversight, auditability, and risk-based approval
• Ability to translate business requirements into technical questions, identify constraints, and involve relevant specialists
• Visible, engaging leadership; strong ownership; pragmatic judgement; confident facilitation and communication; structured, analytical, outcome-focused approach
• Будет плюсом: experience with a digital sandbox, fintech marketplace, AI experimentation platform, or regulated innovation environment; experience in banking, capital markets, corporate banking, or another highly regulated industry; experience operating an AI or innovation portfolio and establishing routes from experimentation into production delivery; knowledge of Azure, Microsoft 365, data platforms, identity, and enterprise architecture patterns; experience working with procurement, legal, operational risk, compliance, information security, architecture, and internal audit stakeholders

• The anticipated salary range is €72,000.00 – €134,000.00; the final offer depends on skills, experience, role scope, location, and relevant market factors
• The role may be eligible for a discretionary incentive award and a competitive benefits package, including pension provision
• Competitive company benefits, including competitive paid leave, private medical insurance, life and invalidity insurance, counselling and coaching services, learning and development opportunities, and career progression opportunities
• Hybrid and flexible working; Sport & Social Clubs; Diversity and Inclusion networks