Vice President, AI Solutions Lead Greater Singapore Area

The Vice President, AI Solutions Lead will lead the discovery, design, testing and rollout of high-impact AI and Generative AI solutions across SMBC and selected customer-facing initiatives. The role sits within the AI Office and combines AI product leadership, business engagement and hands-on solution delivery, supported by sufficient coding and platform knowledge to guide implementation effectively.

This role sits within the AI Solutions department rather than IT. The successful candidate will work closely with business teams to identify priority needs, shape practical AI solutions, coordinate implementation and testing, and drive adoption through rollout and stabilization. The role will partner with IT, architecture, security and vendors for technical enablement while retaining ownership of the product vision, user outcomes and end-to-end solution journey.

Key Responsibilities:

Business Discovery and AI Product Shaping

Partner with business teams to identify pain points, understand user journeys and prioritize AI opportunities against strategic value, feasibility and adoption potential.

Translate business needs into clear product concepts, solution scope, user stories, success measures, delivery roadmaps and rollout plans.

Lead workshops, demonstrations and design sessions to validate requirements, shape the user experience and build stakeholder alignment.

Own the solution journey from discovery and prototype through testing, launch, adoption and post-launch improvement.

AI Solution Design and Configuration

Design and configure practical agentic AI solutions using Microsoft AI Foundry, Copilot Studio, Power Automate and approved coding-enabled tools such as Claude Code.

Create prompts, agent instructions, knowledge grounding, user interactions and automated flows for approvals, notifications, document generation, logging, retries and exception handling.

Connect solutions with SharePoint, Teams, Outlook and approved enterprise data or services using secure APIs and connectors in partnership with IT and platform teams.

Ensure designs incorporate permission-aware grounding, role-based access, maker-checker controls, audit logs, source traceability and appropriate human oversight.

Testing, Readiness and Controlled Release

Define test scenarios and acceptance criteria with the business, Test Engineer and control functions, covering output quality, usability, controls and operational readiness.

Coordinate SIT and UAT, triage feedback and defects, prioritize fixes and confirm readiness for launch.

Apply appropriate coding and configuration standards, environment variables, solution packaging and controlled promotion across Dev, Test, UAT and Production.

Maintain release notes, deployment checklists, regression evidence and traceability so that changes remain controlled and supportable.

Rollout, Adoption and Continuous Improvement

Plan and execute business rollout, including pilot groups, communications, demonstrations, training, user support and hypercare.

Define and track adoption, usage, quality, turnaround time and business outcome measures to assess whether the solution is delivering value.

Use user feedback, monitoring and operational data to prioritize enhancements and improve the product backlog.

Coordinate diagnosis of flow failures, latency, data-access issues and exceptions with technical teams, and ensure that fixes are validated and communicated.

Cross-functional Product and Delivery Leadership

Collaborate with the Product Manager, Test Engineer, architects, IT and security teams, platform owners and vendors to estimate work and deliver sprint commitments.

Maintain a clear product backlog, delivery plan, dependencies, decisions and risks, ensuring that business priorities remain visible throughout delivery.

Provide practical solution direction and hands-on support in configuration, prompting, workflow design and issue resolution where required.

Communicate solution choices, progress, risks and trade-offs clearly to business sponsors, users and technical stakeholders.

Documentation and Handover

Maintain solution designs, interface specifications, configuration records, deployment notes, test evidence, support runbooks and known-error documentation.

Provide knowledge transfer, administrator guidance and production support handover to BAU teams.

Maintain traceability from requirements and controls through build, testing, release and operational monitoring.

Required Qualifications and Experience:

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, Engineering or a related technical field.

7–12 years of relevant experience in AI product delivery, digital transformation, business solution design, enterprise automation or technology consulting, including ownership of solutions from discovery through rollout.

Hands-on delivery experience with Copilot Studio and Power Automate, including APIs/connectors, SharePoint and secure enterprise integration.

Working coding capability in Python and familiarity with JavaScript or TypeScript, sufficient to prototype, configure, review and troubleshoot AI solution components, integrations and workflows.

Practical familiarity with REST APIs, JSON, Git-based version control, authentication concepts, environment configuration and controlled release practices.

Experience building LLM-based applications such as RAG solutions, copilots, knowledge assistants, document intelligence or workflow agents.

Experience with prompt engineering, model or agent evaluation, grounding, tool use, guardrails and human oversight.

Demonstrated ability to lead business testing, manage feedback and defects, coordinate fixes and support rollout in regulated enterprise environments.

Strong stakeholder management skills and the ability to bridge business requirements, architecture, engineering, testing, security and operations.

Preferred:

Experience in banking, financial services or another regulated industry with strong data, security, audit and change-control requirements.

Experience leading cross-functional AI product or solution workstreams while remaining hands-on in design, configuration, testing and rollout.

Exposure to Azure services such as Azure Functions, Logic Apps, API Management, Key Vault, Application Insights and DevOps pipelines.

Familiarity with Responsible AI, model risk, privacy, regulatory expectations and operational resilience.

Relevant certifications such as Microsoft Certified: Azure AI Engineer Associate, Power Platform Solution Architect Expert, Power Platform Developer Associate, Azure Developer Associate or equivalent recognised AI/cloud credentials.