Oliver Wyman - AI Product Enablement Analyst- Kuala Lumpur
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Oliver WymanDescription:
About Oliver Wyman
Oliver Wyman is a global leader in management consulting. With offices in more than 70 cities across 30 countries, the firm combines deep industry knowledge with specialized expertise in strategy, operations, risk management, and organizational transformation. Oliver Wyman works with CEOs and executive teams of leading global organizations to drive lasting impact.
Visit our website for more details about Oliver Wyman: www.oliverwyman.com
Job Overview
The Quotient Inside AI Product Enablement Engineer supports the AI Capability & Adoption function through structured AI experimentation, prompt engineering, workflow testing, and enablement support. This role focuses on reliable execution, technical fluency, and consistent knowledge capture while developing deeper expertise in AI tools and workflows for the Oliver Wyman Centre of Excellence for Quotient Inside.
Working under the direction of the Quotient Inside Product Strategy leadership team and Director of AI Product Enablement, the Engineer contributes to coaching support, prompt refinement, custom GPT testing, and artifact creation that help scale responsible AI usage and adoption across the firm.
This is a hands-on contributor role that emphasizes experimentation, documentation, and quality delivery.
Key Responsibilities :
AI Experimentation & Prompt Engineering
- Execute structured prompt testing and refinement across defined AI use cases the Centre of Excellence may own and manage
- Support configuration and testing of custom GPTs and AI assistants for the Centre of Excellence
- Validate outputs for clarity, consistency, safety, and usability
Workflow Prototyping & Technical Support
- Assist in prototyping lightweight AI workflows under guidance
- Identify basic technical constraints and escalate appropriately
- Support experimentation across AI tools to assess feasibility and usage boundaries
Documentation & Living Exemplars
- Build and maintain prompt libraries, living exemplars, and structured guides for the Centre of Excellence
- Document tested use cases in reusable formats
- Contribute technical examples and demos to training and enablement materials
Coaching Support & Community Engagement
- Support office hours and working sessions
- Help translate user questions into structured AI prompts or Product Strategy team actions and backlog items
- Guide colleagues toward appropriate resources and exemplars
- Support AI coaching and respond to inbound questions
Pattern Awareness & Feedback
- Track recurring questions and usage patterns
- Share structured observations with the AI Product Strategy team leads
- Contribute technical input to decks and enablement documentation
Experience Required
- 2–5 years of experience in analytics, digital enablement, or technology-adjacent roles
- Exposure to AI tools and interest in experimentation
- Experience supporting documentation or analysis work in collaborative, cross functional environments
Skills and Attributes
- AI tool fluency and prompt experimentation
- Comfortable operating within defined processes
- Curious and experimentation driven
- Detail-oriented and reliable in execution
- Analytical mindset and attention to detail
- Clear written communication
- Strong learning orientation
How we rate this
Oliver Wyman - AI Product Enablement Analyst- Kuala Lumpur at Marsh McLennan rates 43 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide which parts of a product should use AI versus a fixed set of rules?
- How do you think about the risk of an AI system in this kind of role failing silently?
- This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
- Tell me about a time an AI tool got something wrong. How did you catch it?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, AI Product, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.
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