Agile Product Manager

Systems Limited

Kuala Lumpur

On-site

MYR 180,000 - 270,000

Full time

18 hours ago
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Job summary

Systems Limited in Kuala Lumpur seeks an Agile Product Manager with 10+ years of PM experience to own the AI engagement outcomes, translating business goals into a prioritized, testable backlog and driving adoption after release.

You will own the backlog for AI engagements, run discovery with clients, define acceptance thresholds, and coordinate data readiness with model work across PoC, pilot and scale.

Qualifications

  • 10+ years product management or product ownership experience.
  • 3+ years on AI/ML or data-intensive products.
  • Fluent in agile delivery (Scrum/Kanban/SAFe).
  • Able to write crisp acceptance criteria for probabilistic outputs.
  • Experience running change management and adoption for complex systems.

Responsibilities

  • Own the product backlog for AI engagements with value-based epics.
  • Translate business outcomes into AI use cases with success criteria.
  • Run discovery with client stakeholders to identify real problems.
  • Define what 'good enough' means for a non-deterministic system with AI.
  • Own the release plan across PoC, pilot and scale with human-in-the-loop.
  • Prioritize data readiness and model work integration.
  • Run sprint ceremonies and maintain team alignment on priorities.
  • Manage scope, timelines and client expectations for performance.
  • Lead adoption, training, rollout comms, and measuring usage.
  • Track value realization and feed insights into the roadmap.
  • Sign off on responsible-AI governance with Governance and Security.
  • Report progress, risk and outcomes to client and firm leadership.

Skills

Backlog management
AI/ML domain understanding
Agile delivery
Stakeholder facilitation
Requirements writing
Data literacy
Risk assessment
Effective communication

Job description

We are seeking a Agile Product Manager with approximately 10+ years of experience in the field. Owns the product outcome of an AI engagement — turning business goals into a prioritized, testable backlog, holding the line on what "working" means for a non-deterministic system, and driving adoption once it ships.

Responsibilities:
  • Own the product backlog for AI engagements — outcome-framed epics, prioritized by value, feasibility and risk
  • Translate business outcomes into AI use cases with explicit success criteria and acceptance thresholds
  • Run discovery with client stakeholders and users to separate real problems from AI-shaped solutions
  • Define what "good enough" means for a non-deterministic system, with AI Assurance and the client jointly
  • Own the release plan across PoC, pilot and scale, including human-in-the-loop and fallback behaviour
  • Prioritize data readiness and integration work alongside model work, not after it
  • Run sprint ceremonies for the delivery pod and keep the team unblocked against a single set of priorities
  • Manage scope, timeline and client expectations when model performance is uncertain
  • Own adoption and change management — training, rollout comms, and measuring real usage
  • Track value realization post-launch and feed it back into the roadmap
  • Own responsible-AI and governance sign-off in the delivery flow, with Governance and Security
  • Report progress, risk and outcomes to client and firm leadership
Requirements:
  • 10+ yrs product management or product ownership, including 3+ yrs on AI/ML or data-intensive products
  • Fluent in agile delivery (Scrum/Kanban/SAFe) and comfortable owning a backlog under real timeline pressure
  • Understands the AI delivery lifecycle — data readiness, evaluation, deployment, monitoring, retraining
  • Technically literate enough to challenge feasibility, cost and latency claims without designing the solution
  • Comfortable writing acceptance criteria for probabilistic outputs — thresholds, guardrails, escalation paths
  • Familiar with AI eval and observability practices well enough to act on the results
  • Working knowledge of responsible-AI, privacy and governance obligations in regulated environments
  • Strong discovery and facilitation skills — workshops, interviews, prioritization with senior stakeholders
  • Data-literate on outcome measurement — instrumentation, adoption metrics, benefit tracking
  • Clear communicator who can hold a client to a decision and say no to scope that will not deliver value
  • Experience running change management and adoption for a system that alters how people work
  • Success metrics: value realized against the business case · adoption/active usage post-launch · release predictability across PoC to scale · client-reported clarity of scope and priorities
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