Job Description

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.