Vice President, AI Solutions Design (AIO)

Reporting to the GM of AI Transformation Office (AIO), Asia, this role will drive the identification, design, and delivery of high-impact AI and Generative AI use cases across SMBC and Customers. This role sits within the AI Office (AIO) and focuses on translating business needs into practical, scalable AI solutions for both internal stakeholders and selected client-facing initiatives.

The Role Responsibilities

The Vice President, AI Solutions Design will drive the identification, design, and delivery of high-impact AI and Generative AI use cases across SMBC and Customers. This role sits within the AI Office (AIO) and focuses on translating business needs into practical, scalable AI solutions for both internal stakeholders and selected client-facing initiatives.

This is a business-led AI role, not a traditional IT infrastructure position. The successful candidate will work closely with business units, product teams, and internal/external technology partners to shape use cases, define solution approaches, and ensure successful hands-on delivery of AI solutions that create measurable business value.

Key Responsibilities

1. Business Needs Identification & Use Case Development

• Partner with business units to identify, assess, and prioritize AI opportunities aligned to strategic objectives.
• Conduct business analysis, value assessment, and feasibility evaluation for AI use cases.
• Translate business problems into clear AI solution concepts and implement roadmaps. Define success metrics, ROI, and adoption strategies.

2. AI Solution Design & Hands-on Delivery

• Design practical AI and GenAI solutions including:

• Copilots and workflow automation
• Knowledge assistants and document intelligence
• Decision support and analytics use cases
• Customer and operations productivity solutions

• Work hands-on with delivery teams to develop prototypes, pilots, and production implementations.
• Support activities such as prompt design, model selection, evaluation, and solution configuration.
• Ensure solutions are scalable, secure, and aligned to enterprise standards.

3. Collaboration with Technology Teams & Partners

• Work closely with internal IT, data, and platform teams to enable solution implementation.
• Collaborate with external vendors, system integrators, and client technology teams where applicable.
• Act as the functional bridge between business stakeholders and technical delivery teams.
• Support integration of AI solutions into existing business processes and systems.

4. Internal & External Engagement

• Support AI initiatives for internal transformation as well as selected client or partner-facing solutions.
• Facilitate workshops, ideation sessions, and use case discovery engagements.

5. Governance & Responsible AI

• Ensure solutions comply with SMBC policies, regulatory expectations, and Responsible AI principles.
• Incorporate controls such as data governance, model transparency, human oversight, and risk management.
• Work with risk, compliance, IT, security and model governance teams during solution implementation.

Qualifications & Experience

Required

• Bachelor’s degree in Computer Science, Statistics, Engineering, Data Science, or related field.
• 10+ years of experience in AI, digital transformation, or technology consulting roles with strong business engagement.
• Proven hands-on experience delivering AI or Generative AI solutions from use case definition through implementation.
• Practical experience with:
  • LLM-based applications (RAG, copilots, automation, knowledge assistants)
  • Prompt engineering and model evaluation
  • AI solution prototyping and deployment on enterprise platforms (e.g., Azure OpenAI, AWS, or similar)
• Experience working closely with business stakeholders to translate requirements into deployed solutions.
• Experience collaborating with cross-functional teams including IT, data, and external vendors.
• Certifications (Required / Strongly Preferred) - Relevant AI or cloud certifications such as:
  • Microsoft Azure AI Engineer / Azure OpenAI
  • AWS Machine Learning Specialty
  • Google Professional Machine Learning Engineer
  • Equivalent recognised AI/GenAI certifications
• Preferred:
  • Experience in banking, financial services, or other regulated industries.
  • Experience in consulting or client-facing solution development.
  • Familiarity with Responsible AI, model risk, and regulatory considerations.

Key Competencies:

• Strong business analysis and problem-solving capability
• Ability to translate business needs into practical AI solutions
• Hands-on delivery mindset with execution focus
• Stakeholder management and communication
• Collaborative approach across business, IT, and external partners
• Outcome-driven with focus on measurable value