AI Product Owner

TP. Ho Chi Minh

Posted November 06, 2026

Role Summary

The Product Owner – AI Assistants owns company's conversational AI platform — voice and text capabilities — as a shared, reusable service for the wider company. Business units own the specific products and use cases built on top of the platform; IT/Dev owns technical development. This role owns everything in between: turning business demand into clear requirements, setting the standards that keep the platform reusable and consistent, holding knowledge bases and AI governance to a high bar, and running the backlog, planning, and delivery cadence that keeps IT/Dev, vendors, and business stakeholders aligned.
This is a business-acumen-led role. A solid foundational understanding of AI and conversational technology is essential to set direction and ask the right questions — deep technical or engineering depth is not required, as that sits with IT/Dev.

What You'll Own

The AI platform itself (voice and text capabilities) as a shared, reusable service for the company.
Standards for reusable AI solutions and knowledge bases, so business units build on shared foundations rather than duplicating effort.
AI governance for the platform — guardrails, access, risk, and compliance for use in a regulated lending environment.
The prompt / agent / assistant catalog — versioning, approval, and reuse standards.
Backlog, sprint reviews, and planning cadence with IT/Dev, translating business demand into buildable requirements.

KEY RESPONSIBILITIES

1. Platform Ownership & Reuse Standards

Own voice, text, and adjacent AI capabilities as a shared enterprise platform, not a business-unit-specific build.
Set and enforce reuse standards so business units build on shared platforms rather than duplicating parallel solutions.
Hold the line on the ownership model: business owners own their products and use-case outcomes on top of the platform; IT/Dev owns technical development; this role owns the standards, requirements, and delivery cadence that connect the two.

2. Business Demand & Expectation Management

Translate open-ended "we want AI" requests from business stakeholders into concrete, prioritized use cases with clear value and dependencies.
Actively manage business expectations of what the platform can and cannot deliver, given data, timeline, and platform constraints.
Convert business ideas into structured requirements that IT/Dev can build against.

3. Data, Knowledge Base & Reuse Readiness

Set standards for how business units structure and maintain knowledge bases so they stay accurate, current, and reusable across use cases.
Orchestrate the data gathering, source mapping, and validation practices the platform depends on.
Establish golden datasets and evaluation approaches so platform quality stays measurable over time.

4. AI Governance & Lifecycle

Set guardrails, access, risk, and compliance controls for AI use appropriately to a regulated lender.
Own the prompt / agent / assistant catalog — versioning, approval, and reuse standards.
Manage the capability lifecycle: monitoring, model routing decisions, and safe retirement of underperforming prompts, agents, or models.

5. Delivery & Planning Leadership

Own the platform roadmap, backlog, dependencies, and adoption across delivery rounds.
Run backlog grooming, sprint reviews, and planning cycles with IT/Dev engineering and external vendors, with final vendor authority sitting with the Head of AI Program.
Coordinate across business owners, IT/Dev, and vendors to keep delivery aligned and on track.

6. Value, Adoption & Reporting

Define adoption and reuse metrics for the platform; track value realization across use cases.
Report portfolio health and value delivered to the Head of AI Program.

What Success Looks Like

Growing adoption and reuse of the platform across business units, rather than duplicate parallel builds.
Consistent, high-quality knowledge bases and reusable AI solution standards in active use.
A functioning prompt / agent / assistant catalog with clear versioning and approval standards.
A predictable backlog, planning, and delivery cadence that IT/Dev and business stakeholders can rely on.
Business owners consistently convert ideas into clear, buildable requirements through this role.

REQUIREMENTS

Good experience as product owner/product manager in Consumer Finance/Banking/Fintech with experience building automation products/AI.
Bachelor's or Master's degree in Business, Computer Science, Engineering, or related field.
Strong ability to translate ideas into clear and prioritized requirements.
Experience building automation products or foundational understanding of conversational AI, AI governance, and related tools is a good plus
Experience managing backlog, sprint reviews, planning cycles, and agile delivery cadence.
Experience with Agile project management tools (JIRA, Asana, Trello, or similar).
Strong stakeholder management, communication, presentation.
Good English skills

COMPENSATIONS & BENEFITS

If you are referred for this position by our Employee/Recruitment Collaborator, please apply via this LINK.

If you are an internal candidate, please apply via this LINK.

Otherwise, please click the Apply button as below for application.

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