AI Product Manager / PMO

About the role

Hytech, a management consulting firm with offices in Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus and Dubai, is hiring an AI Product Owner / PMO in Singapore. You will own the end-to-end lifecycle of AI products such as Generative AI, Fraud Intelligence, Agent Systems and Growth Automation, acting as the link between business strategy, engineering and client outcomes while managing several concurrent initiatives.

Key responsibilities

• Define product vision, roadmap and success metrics for AI solutions, balancing technical feasibility with business impact.
• Run market and client discovery, validate solutions through rapid prototyping and A/B testing.
• Own PRDs, user stories and acceptance criteria, and prioritize the backlog by effort and value.
• Set up adoption frameworks and ROI tracking for deployed AI products.
• Implement agile/hybrid delivery frameworks with stage gates, risk logs and dependency mapping.
• Monitor portfolio health with KPIs such as on-time delivery, budget variance, resource utilization and technical debt.
• Facilitate workshops with engineering, data science, legal/compliance and client teams, and curate reusable assets like templates and MLOps standards.
• Act as AI product evangelist: executive briefings, user training and change management.
• Partner with platform teams so AI solutions meet scalability, explainability and regulatory requirements.

Required profile

• 5+ years in product management or technical program management, with at least 2 years on AI/ML products (GenAI, NLP, predictive systems).
• Proven ownership of product metrics and governance of multi-project portfolios.
• Experience in consulting or fintech, able to scope solutions under tight deadlines and ambiguous requirements.
• Ability to prototype without coding (no-code tools) and a track record in resource forecasting, risk mitigation and post-mortems.

Required skills

• Jira, Asana and Power BI.
• LLM patterns: prompt engineering, RAG optimization, agent orchestration and evaluation frameworks (HELM, RAGAS).
• MLOps basics (data versioning, drift monitoring) and CI services (AWS SageMaker, Azure ML).