The Generative AI Use Case Design Lead is responsible for identifying, validating, and shaping high‑impact Generative AI and Agentic AI use cases across CIMB. This role sits at the intersection of product strategy, user experience, design thinking, and applied AI innovation. It requires deep customer empathy, strong problem‑framing skills, and the ability to translate business challenges into human‑centred, AI‑enabled solutions.

The role drives user research, journey mapping, competitor and market scanning, and rapid prototyping to ensure CIMB develops differentiated, scalable, and compliant AI products. Working closely with business stakeholders, data scientists, engineers, and product managers, the Use Case Design Lead ensures each AI initiative is rooted in validated customer needs, operational realities, and measurable business value.

Strong skills in Agile user research, product management and a deep understanding of data and AI technologies is a must. Experience in the banking or financial services industry is important but ultimately, not mandatory. 

A. Generative AI Use Case Discovery & Strategy

• Lead structured discovery processes to identify and prioritise high‑value AI use cases across business units and support functions.
• Conduct competitive and industry research to benchmark global GenAI innovations and identify opportunities for CIMB differentiation.
• Translate business problems into clear problem statements, hypotheses, and well‑defined opportunity areas.
• Facilitate design thinking workshops, ideation sessions, and co‑creation engagements with users and SMEs.

B. User Research & Experience Design

• Drive end‑to‑end user research, including interviews, contextual inquiry, shadowing, and usability testing.
• Map customer and employee journeys, identifying friction points where Generative or Agentic AI can create transformative value.
• Ensure all AI solutions deliver ethical, human‑centred experiences aligned with CIMB’s brand and regulatory obligations.

C. GenAI Product Concepting & Prototyping

• Translate research insights into AI product concepts, mockups, and low‑fidelity prototypes for early validation.
• Collaborate with data scientists, engineers, and UX designers to build rapid AI prototypes using available platforms and tools.
• Test and iterate prototypes to achieve clear product‑market and usability validation before full build‑out.

D. Business Case Development & Prioritisation

• Develop measurable value frameworks including cost savings, revenue uplift, productivity, customer experience improvements, and risk mitigation.
• Articulate the business case, success metrics, and feasibility assessments.
• Support prioritisation discussions with GDAI leadership and other stakeholders.

E. Execution Support & Cross‑Functional Collaboration

• Partner with GenAI Product Managers and delivery teams to ensure research insights and design intent are preserved through build and deployment.
• Support compliance, model risk, governance, and technology teams by ensuring design artefacts and decision logs meet regulatory expectations.

F. Thought Leadership & Capability Building

• Act as an internal evangelist for human‑centred AI design, continuously promoting best practices in research, experimentation, and validation.
• Coach business teams on how to identify, evaluate, and implement AI opportunities.
• Contribute to CIMB’s external leadership position through insights, frameworks, and innovation showcases.

 Financial

• Direct impact on value creation through validated AI use cases contributing to revenue uplift, cost reduction, and process efficiency.
• Influences investment decisions on AI initiatives.

Non‑Financial

• Drives discovery and validation for 10+  AI use cases annually.
• Impacts customer and employee experience through AI‑enabled service models.
• Supports governance and compliance objectives of GDAI. 
• Influences cross‑functional collaboration across product, operations, technology, compliance, and business divisions.

Qualifications 

(Basic Degree/Diploma etc)

• Certification in Project Management (e.g., PMP, PRINCE2) or Agile methodologies (e.g., Certified ScrumMaster) is desirable.

• 10+ years of experience in product management, design, data, analytics or related field. 
• Proven experience leading projects related to data analytics, machine learning, or AI.
• Experience with project management methodologies such as Agile, Lean, Scrum, or Waterfall.

Competencies/Skills 

(Essential to succeed in this job)

Technical/Functional Skills:

• Strong understanding of LLMs, RAG pipelines, multimodal models, prompt engineering, and Agentic AI frameworks. 
• Understanding of AI governance, model risk, data privacy, bias detection, explainability, and regulatory requirements 
• Expertise in qualitative and quantitative research (interviews, observation, journey mapping, usability testing).
• Skilled at translating business challenges into validated AI use cases and measurable value hypotheses.
• Understanding of data pipelines, APIs, and model integration to collaborate effectively with engineers and data scientists.
• Capability to perform market and competitor analyses, emerging technology tracking, and benchmark studies relevant to GenAI.

Personal skills (Soft Competencies [Core/Leadership]):

• Forward‑looking mindset to identify innovative, high‑value AI opportunities for CIMB.
• Ability to balance innovation with regulatory, ethical, and operational constraints.
• Excellent communication and stakeholder management skills 
• Comfortable navigating between business, technology, governance, and regulatory teams.
• Highly organized, with ability to manage multiple discovery tracks concurrently.
• Strong ideation skills with a structured, analytical approach to validation and prioritisation.