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CAREER OPPORTUNITIES > MALAYSIA

Technical Product Manager – AI Engineering & Operations

The Technical Product Manager (Enterprise AI Solutions) serves as the bridge between Apexone business leadership and the AI engineering team. This individual maps real business requirements — such as automated credit scoring, dynamic merchant reward logic, fraud detection, and market intelligence — into actionable engineering sprints.

You will own the product roadmap for Apexone's Enterprise AI capabilities across our flagship platforms: Enterprise AI, Digital Banking & Fintech Ecosystem, Apexium Centralized Exchange (CEX), Universal Loyalty Ecosystem, Smart Manufacturing IR4.0, and Smart City initiatives. You will translate complex business objectives into clear product requirements, prioritize features based on business impact and technical feasibility, and ensure all AI products comply with sovereign data regulations.

This role requires a unique blend of product management discipline, generative AI expertise, and deep operational familiarity with financial software compliance. You will work closely with AI Engineers, Forward Deployed Engineers (FDE), Solution Architects, and business stakeholders to deliver AI products that drive measurable business outcomes while maintaining strict data sovereignty and regulatory compliance.

Enterprise AI Solutions

LOCATION

DEPARTMENT

REPORTS TO

One City, Malaysia (with regional travel as required)

AI Engineering & Operations

Chief Technology Officer (CTO)

Core Responsibilities

Key Role Objectives:
A. Enterprise AI Feature Mapping & Product Strategy

  • High-Value Feature Identification: Identify and prioritize high-value AI features for flagship platforms:

    • Universal Loyalty: Dynamic merchant reward logic, personalized offer engines, predictive member spending models, gamification optimization.

    • Centralized Exchange CEX (Apexium): Automated market intelligence charts, smart trading bot configurations, portfolio optimization, sentiment analysis dashboards.

    • Digital Bank: Automated fraud detection profiles, AI-driven credit scoring, personalized financial recommendations, predictive customer churn alerts.

    • Smart Manufacturing: Predictive maintenance alerts, quality defect detection, supply chain demand forecasting, production optimization.

    • Smart City: Citizen service personalization, traffic flow prediction, public safety analytics, urban resource optimization.

  • Product Roadmap Development: Develop and maintain a 12-18 month product roadmap for Enterprise AI capabilities, balancing quick wins with long-term strategic investments.

  • Business Case Development: Build compelling business cases for AI features — including ROI projections, TCO analysis, competitive positioning, and alignment with client digital transformation agendas.

  • Client Requirement Translation: Translate client business requirements from solution architects, pre-sales consultants, and client executives into detailed product specifications and engineering user stories.

B. Sovereign Compliance & Data Governance

  • Regulatory Alignment: Ensure all AI product features strictly align with regional data residency guidelines — Malaysia PDPA, Oman PDPL, GDPR, and GCC data sovereignty frameworks — verifying that customer information never leaks outside authorized network lines.

  • Privacy-by-Design: Embed privacy and compliance requirements into product requirements from the outset, ensuring AI features are designed for regulatory approval.

  • Audit & Transparency: Define product requirements for model explainability, audit trails, and compliance reporting — enabling clients to demonstrate regulatory compliance to Central Banks, government agencies, and auditors.

  • Sovereign AI Product Design: Design AI products that can be deployed on private infrastructure with zero data leakage, supporting Apexone's Forward Deployed Engineering (FDE) model.

C. Model Performance Tracking & Product Optimization

  • Live Performance Monitoring: Monitor live user interactions with AI features to flag model hallucinations, broken logic paths, performance degradation, and accuracy issues.

  • User Feedback Integration: Establish feedback loops to capture user sentiment, feature requests, and friction points — incorporating insights into the product roadmap.

  • Continuous Improvement: Adjust the development roadmap to continually improve accuracy, user satisfaction, and business outcomes based on real-world performance data.

  • A/B Testing & Experimentation: Design and manage A/B tests for AI features to validate hypotheses, measure impact, and drive data-informed product decisions.

  • KPIs & Success Metrics: Define and track product KPIs — adoption rates, user engagement, accuracy metrics, business impact (e.g., fraud reduction %, cost savings, revenue lift).

D. Stakeholder & Cross-Functional Collaboration

  • Business-Technical Bridge: Serve as the primary liaison between business stakeholders, AI Engineers, Forward Deployed Engineers (FDE), Solution Architects, and client teams.

  • Engineering Collaboration: Work closely with AI Engineers to refine requirements, validate technical feasibility, and ensure successful delivery of AI features.

  • Executive Reporting: Provide regular product updates to C-suite leadership — including roadmap progress, feature releases, performance metrics, and strategic recommendations.

  • Client Engagement: Engage with client stakeholders to understand pain points, gather requirements, present product roadmaps, and secure buy-in for AI feature adoption.

  • Go-to-Market Strategy: Partner with marketing, sales, and pre-sales teams to develop go-to-market strategies for new AI features — including positioning, messaging, and client demonstration materials.

E. Market & Technology Intelligence

  • Competitive Analysis: Continuously track competitive AI product offerings in FinTech, Loyalty, and Enterprise markets — identifying gaps and opportunities for differentiation.

  • Emerging Technology Evaluation: Evaluate emerging AI technologies, frameworks, and models (including the latest DeepSeek series, Llama, Qwen, Mistral) to assess their potential for Apexone's product roadmap.

  • Industry Trends: Stay abreast of industry trends in Enterprise AI, Generative AI, MLOps, and AI governance — translating insights into product strategy recommendations.

Required Qualifications & Experience:

  • 5+ years of product management experience in enterprise software, SaaS platforms, or technology-driven environments

  • Proven experience launching generative AI features or AI/ML products in production environments — preferably in FinTech, Banking, E-commerce, or Enterprise platforms

  • Deep operational familiarity with financial software compliance — including PCI-DSS, ISO/IEC 27001, PDPA/PDPL/GDPR, and financial regulatory frameworks

  • Agile product management expertise — including backlog management, sprint planning, user story writing, and cross-functional team coordination

  • Strong understanding of AI/ML concepts — including large language models (LLMs), RAG pipelines, multi-agent systems, and MLOps — sufficient to engage credibly with AI engineers

  • Excellent communication skills — ability to translate complex technical concepts into clear business language for executives and clients

  • Preferred Qualifications:

    • Experience with sovereign AI deployments in regulated industries (FinTech, Banking, Government, Healthcare)

    • Experience with 01.AI, DeepSeek, Llama, or similar open-source model ecosystems

    • Experience with FinTech/Banking platforms — digital banking core, CEX exchanges, payment systems, lending platforms

    • Experience with Agile/Scrum certification — Certified Scrum Product Owner (CSPO) or SAFe® Product Owner/Product Manager

    • Experience with government digital transformation initiatives and public sector procurement

    • Experience with product analytics tools — Mixpanel, Amplitude, Google Analytics

    • Domain expertise in one or more: Enterprise AI, Digital Banking, Crypto/CEX, Loyalty Programs, Smart Manufacturing, Smart City

Success Criteria in First 12 Months:

  • Successfully define and deliver at least 2-3 major AI feature releases across flagship platforms (Digital Bank, CEX, Loyalty, or Smart Manufacturing)

  • Establish product roadmap for Enterprise AI capabilities with clear prioritization, milestones, and resource requirements

  • Achieve >70% user adoption for at least one newly launched AI feature

  • Implement product performance tracking framework with KPIs, dashboards, and feedback loops for continuous improvement

  • Successfully translate client AI requirements into engineering user stories for at least 3 client engagements

  • Establish compliance-first product design framework ensuring all AI products meet data sovereignty and regulatory requirements

  • Build strong relationships with AI Engineering team, Solution Architects, and FDE teams — enabling effective cross-functional collaboration

  • Develop go-to-market strategy for at least one AI product offering, including positioning, messaging, and client demonstration materials

EMPLOYMENT TYPE: FULL-TIME, PERMANENT

APPLICATION PROCESS

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Ready to lead enterprise transformation in Oman?

Our recruitment process: CV Review → Technical Assessment → Leadership Interview → Offer

Apexone is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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