About
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.
Responsibilities
•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
Requirements
•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
Nice to have
•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
Conditions
•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
