About Hytech
Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services companies. We provide comprehensive consulting solutions, as well as middle- and back-office support, to empower our 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
You will own the end-to-end lifecycle of AI products (Generaative AI, Fraud Intelligence, Agent Systems, Growth Automation) and govern cross-functional delivery as thenexus between business strategy, engineering, and client outcomes. In this dual-role capacity, You'll: Shape AI product strategy by translating ambiguous business challenges into prioritized, value-driven AI solutions. Orchestrate delivery rigor as PMO - ensuring timelines, resources, and risks are managed for 3-5 concurrent AI initiatives. Bridge the last mile 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/client discovery to identify high-value AI use cases; validate solutions via 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 & ROI tracking mechanisms for deployed AI products (e.g., reduction in fraud losses, 30% content ops efficiency gain).
- Implement standardized delivery frameworks for AI projects (agile//hybrid), including stage gates, risk logs, and dependency mapping.
- Monitor portfolio health via KPIS: 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: conduct executive briefings, user training, and change management sessions.
- Translate complex AI capabilities into business outcomes for non-technical stakeholders (e.g., 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 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 (tools: Jira, Asana, Power BI).
- Mastery in stakeholder negotiation - ability to align engineering, businness leads, and C-suite on priorities amid ambiguity.
- Hands-on understanding of LLM application patterns: prompt engineerring, 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 likeVoiceflow, Mendix) to validate concepts pre-engineering.
- PMO rigor: Track record in resource forecasting, risk mitigation, andd post-mortem analysis for complex tech initiatives.
