ai-native product manager

Overview

Who you'll be working for

What requirements you'll need to be eligible

• 5+ years of software product management experience, with a track record of guiding products from discovery through delivery.
• Practical understanding of how LLMs work — you know what a context window is, why AI outputs can be inconsistent, and how to write clear instructions that get reliable results from AI tools.
• Strong analytical mindset with a passion for user-centric design and the ability to balance speed with quality.
• Excellent written and verbal communication skills in English, with the ability to articulate precise requirements to both human teams and AI systems.

LANGUAGE

Proficiency in Chinese (Mandarin) is valued for day-to-day collaboration with our China headquarters. Candidates without Mandarin who demonstrate strong cross-cultural communication skills are equally welcome.

What you'll be doing on the job

The Malaysia AI Innovation Center is the overseas R&D hub of our AI Business Group, localizing and scaling AI products across ASEAN markets. We are looking for a Product Manager who works at the intersection of two dimensions:

First, you are a Product Manager for AI products — you own the lifecycle of AI-powered solutions (intelligent agents, AI+industry platforms), translating real business pain points into clear product strategies, roadmaps, and delivery milestones.

Second, you are a Product Manager powered by AI — you use AI tools as core instruments of your own craft. Whether it’s using LLMs for market research, building rapid prototypes with AI generation tools, or writing specifications clear enough for both humans and AI agents to execute, AI is how you work, not just what you build.

You don’t need to be a deep technical expert. What matters is that you understand AI’s practical capabilities and limitations, communicate precisely with engineering teams, and care deeply about solving real customer problems.

KEY RESPONSIBILITIES

• Business Insight: Deeply understand industry clients and regional customers’ business pain points. Identify where AI can create meaningful value, recommend practical technology approaches, and drive the integration of AI capabilities with existing business systems.
• AI Technical Understanding: Maintain a working understanding of how large language models, retrieval-augmented generation (RAG), and AI agent architectures function. You don’t need to build these systems, but you need to assess what AI can and cannot do reliably, evaluate feasibility and cost, and collaborate effectively with engineering teams.
• AI Product Design: Translate customer requirements into clear AI product definitions. Lead product planning from zero to one: iteration roadmaps, delivery milestones, and prioritization of features. Produce clear PRDs, specification documents, and usage guidelines that both human developers and AI tools can work from.
• AI Product Solution Design: Design end-to-end product solutions integrated with customer business workflows. Package successful solutions into reusable templates and frameworks. Serve as the bridge between engineering (technical details) and business teams (value outcomes).
• Team Collaboration & Project Delivery: Coordinate across R&D, design, testing, delivery, and operations teams. Drive the full cycle from prototype review through internal testing, pilot rollout, and optimization. Translate business requirements into language engineers can act on, and resolve issues as they arise.

WHAT YOU CAN LEARN HERE

We will invest in your growth in these areas. Prior exposure is a plus, not a prerequisite:

• Specification-driven development practices — writing machine-parseable specs that directly drive AI agent execution.
• Hands-on use of AI prototyping tools (Lovable, Bolt.new, v0, Replit) for rapid MVP development.
• AI safety principles, responsible AI practices, and ASEAN regulatory frameworks (Malaysia PDPA).
• Multi-market product localization strategies for Southeast Asian markets.

Consultant Contact