Digital Product Owner - Digital Operations

MSIG ASIA PTE. LTD.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

MSIG Asia Pte. Ltd. seeks an experienced leader to own end-to-end delivery of a digital operations platform across APAC.

You will bridge business strategy, operations, and software engineering by embedding AI capabilities into core workflows while delivering high-velocity, automated processes with strong STP. You will build AI-native delivery squads, define roadmaps, manage cross-functional teams, and drive adoption of responsible AI practices, enabling scalable, cost-efficient operations across

Qualifications

• Bachelor’s degree in Business, Information Technology, Computer Science, Engineering, or a related discipline.
• Professional certifications such as CSPO, SAFe Product Owner/PM, Lean, or Six Sigma.
• AI-related certifications.
• 10+ years of experience leading product teams and delivering large-scale digital platforms across cross-functional workstreams.
• Experience in insurance operations, workflow automation, and STP initiatives.
• Experience initiating and driving strategic projects to completion with minimal guidance.
• Experience managing onshore, offshore, and vendor delivery teams.
• Proficiency in using AI tools as part of product development.
• Demonstrated ability to integrate AI tools to optimize workflows and drive measurable impact.
• Experience adhering to responsible AI practices.
• Demonstrated ongoing AI skill development.
• Experience analysing, interpreting, and leveraging data for strategic decisions.

Responsibilities

• Own a multi-year digital operations roadmap across APAC.
• Lead product and delivery roadmaps for digital operations across countries.
• Re-engineer operational processes with responsible AI, automation, and STP.
• Translate business needs into use cases and delivery scope to reduce waste and improve efficiency.
• Define and track KPIs linked to lean performance, including customer experience and cost-to-serve.
• Orchestrate complex operations with AI automation and human oversight.
• Define target operating model and transition plans for sustainable adoption.
• Drive lean AI transformation and measurable ROI with business leaders.
• Lead high-performing AI-native teams with governance across sites.

Skills

Delivery leadership

Product ownership

Cross-functional leadership

AI in workflows

Data-driven decision making

Strategy & roadmaps

Change management

Vendor/onshore-offshore governance

Responsible AI practices

Education

Bachelor’s degree in Business/IT/CS/Engineering

Tools

AI tools

Workflow automation

Job description

Operational excellence is a core pillar of MSIG's digital ambition, rooted in a lean culture and an AI-native operating model that continuously drives waste elimination, standardisation, and sustainable, scalable operations. As MSIG continues to build a regional digital insurance distribution platform to deliver products, automation, data-driven insights, and standardised technology solutions at scale across APAC, this role will begin by owning the end-to-end delivery of the platform across multiple markets in APAC. Over time, the role will evolve to drive end-to-end process automation, operational waste reduction, and digital operations modernisation across Digital Consumer Insurance. This role bridges business strategy, operational excellence, and software engineering by embedding AI capabilities into core workflows. The successful candidate will lead high-performing delivery squads, leveraging AI-augmented development tools to maximize velocity while delivering automated operations process with high Straight-Through Processing (STP) rates and lower cost-to-serve.

Key Responsibilities

Digital Operations Strategy & Product Leadership

• Digital Operations Roadmap: Own a multi-year digital operations roadmap across APAC countries and functions.

• Product & Delivery Roadmaps: Lead product and delivery roadmaps for digital operations, proactively managing risks, dependencies, and constraints to support scalable and standardised digital operational processes that enable faster deployment across countries.

• Process Re-engineering: Re-engineer operational processes and workflows with responsible AI, automation, and straight-through processing (STP), from business case through redesign to benefit realisation.

• Use Case Creation: Translate business needs and operational pain points into use cases and delivery scope that reduce waste, improve efficiency, and increase reliability across the digital value chain.

• Performance Metrics: Define and track KPIs connected to lean performance drivers, including customer experience, productivity, stability, and cost-to-serve, while establishing structured continuous improvement feedback loops with country teams.

• Operations Execution: Orchestrate complex operations execution across cross-functional teams and functions by combining AI automation with strategic human oversight (human in the loop), maximising efficiency in a fluid, fast-evolving environment.
• Build–Operate–Transfer Model: Define the target operating model, phase strategy, and BU ownership plan to enable a structured handover and sustainable local adoption.

Operational Efficiency & Business AI Transformation

• Drive Lean AI Transformation: Lead end-to-end operational reviews across Digital Consumer workflows to eliminate waste, reduce manual rework and bottlenecks, and redesign processes through responsible AI, automation, and STP.

• Deliver Measurable Business Impact: Partner with business leaders to prioritise and launch high-value AI use cases, with clear ROI metrics tracking cycle time, transaction cost, accuracy, and efficiency gains.

High-Performance, AI-Augmented Delivery Leader

• Team & Delivery Leadership: Build high-performing, AI-native teams with clear ownership, execution discipline, and strong onshore/offshore governance.

• AI-Augmented Delivery: Use responsible AI tools and practices to improve squad velocity, engineering quality, sprint output, and organisational capability at scale.

• Technical Execution: Translate business strategy into user stories, process flows, data requirements, and acceptance criteria while optimising the delivery pipeline and reducing operational waste.

Operational Adoption & Change Management

• Change Adoption & Readiness: Drive frontline readiness, hands-on training, and adoption support across claims adjusters, servicing teams, and BUs to ensure effective uptake of AI tools.

• Governance & Ownership Transfer: Establish human-in-the-loop controls, fallback protocols, risk frameworks, playbooks, and readiness tracking to enable compliant AI use and sustainable BU ownership.

Risk, Compliance & Operational Readiness

• Risk & Delivery Governance: Proactively manage risks, issues, dependencies, blockers, documentation, approvals, audit trails, and governance evidence across delivery activities.

• Operational Readiness & Compliance: Support platform readiness, operational controls, security requirements, compliance reviews, and business go-live preparation with relevant teams.

Requirements

• Bachelor’s degree in Business, Information Technology, Computer Science, Engineering, or a related discipline

• Professional certifications such as Certified Scrum Product Owner (CSPO), SAFe Product Owner / Product Manager, Lean, or Six Sigma

• AI-related certifications

• At least 10 years of experience leading high-performing product teams and delivering large-scale digital platforms across complex, cross-functional workstreams.

• Experience within the insurance industry, with exposure to insurance operations (underwriting, claims, policy administration), workflow automation, and STP initiatives

• Experience initiating and driving strategic projects to completion with minimal guidance

• Experience managing onshore, offshore, and vendor delivery teams.

• Proficiency in using AI tools as part of day-to-day product development and general productivity workflows

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration), and awareness of emerging AI technologies and trends

• Experience analysing, interpreting, and leveraging data to support strategic decision-making