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Open nowPosted 10 hours ago

AI Product Manager / PMO

Fuku

Where
Singapore
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Your applicationOpen nowAI Product Manager / PMOFuku · Singapore

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Share of postings closed within
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  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted 10 hours ago

The posting

About Hytech

Hytech is a leading management consulting firm headquartered in Australia and Singapore, specializing in digital transformation for fintech and financial services companies. The firm provides comprehensive consulting solutions, as well as middle- and back-office support, to empower clients with streamlined operations and cutting-edge strategies. With a global team of over 2,000 professionals, Hytech has established a strong presence worldwide, with offices in Australia, Singapore, Malaysia, Taiwan, Philippines, Thailand, Morocco, Cyprus, Dubai, and more.

About the Role

As the AI Product Owner/PMO, you will be responsible for the end-to-end lifecycle of AI products, including Generative AI, Fraud Intelligence, Agent Systems, and Growth Automation. You will serve as the nexus between business strategy, engineering, and client outcomes, shaping AI product strategy and orchestrating delivery rigor across multiple concurrent initiatives. This dual-role capacity requires you to translate ambiguous business challenges into prioritized, value-driven AI solutions, manage timelines and resources, and bridge the gap between technical capabilities and business value through stakeholder alignment, ROI tracking, and adoption frameworks.

Key Responsibilities

- Define product vision, roadmap, and success metrics for AI solutions (e.g., GenAI copilots, fraud detection engines, autonomous agent workflows), balancing technical feasibility with business impact. - Conduct market and client discovery to identify high-value AI use cases; validate solutions through rapid prototyping and A/B testing. - Own product requirements documentation (PRD), user stories, and acceptance criteria; prioritize backlog based on effort/value analysis. - Establish adoption frameworks and ROI tracking mechanisms for deployed AI products (e.g., reduction in fraud losses, 30% content operations efficiency gain). - Implement standardized delivery frameworks for AI projects (agile/hybrid), including stage gates, risk logs, and dependency mapping. - Monitor portfolio health via KPIs such as on-time delivery rate, budget variance, resource utilization, and technical debt ratio. - Facilitate cross-functional alignment workshops with engineering, data science, legal/compliance, and client teams to resolve blockers. - Curate reusable assets (templates, playbooks, MLOps standards) to accelerate future AI deployments. - Act as the AI product evangelist by conducting executive briefings, user training, and change management sessions. - Translate complex AI capabilities into business outcomes for non-technical stakeholders (e.g., explaining how graph-based fraud detection reduces false positives by 40%). - Partner with platform teams to ensure AI solutions meet scalability, explainability, and regulatory requirements (e.g., model audit trails).

Required Qualifications

- 5+ years in product management or technical program management, with at least 2 years focused on AI/ML products (GenAI, NLP, predictive systems). - Proven experience owning product metrics (adoption rate, feature usage, ROI) and governing multi-project portfolios using tools such as Jira, Asana, and Power BI. - Mastery in stakeholder negotiation, with the ability to align engineering, business leads, and C-suite on priorities amid ambiguity. - Hands-on understanding of LLM application patterns, including prompt engineering, RAG optimization, agent orchestration, and evaluation frameworks (e.g., HELM, RAGAS). - Familiarity with MLOps pipelines (data versioning, drift monitoring) and CI services (AWS SageMaker, Azure ML). - Experience in consulting or fintech environments, adept at scoping solutions under tight deadlines and ambiguous requirements. - Ability to prototype without coding (e.g., using no-code tools like Voiceflow, Mendix) to validate concepts before engineering. - Demonstrated PMO rigor, with a track record in resource forecasting, risk mitigation, and post-mortem analysis for complex tech initiatives.

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