AI-First Participant Operations Specialist

Why PayNet / Why Now

• National payments infrastructure building the next generation of Malaysia's digital financial ecosystem
• Open Finance is creating new operating models that require support, service, and participant engagement at scale
• Traditional operations teams are no longer enough. The opportunity is to design operations that are AI-native from day one, not manually scaled over time
• Advances in AI agents, automation, and orchestration technologies make it possible to rethink how participant support, service management, and operational knowledge are delivered
• A rare opportunity to build an operational function from a blank page using AI as a core capability, not an afterthought

TL;DR

• Build and operate an AI-first participant operations function from the ground up
• Design how AI agents, humans, automation, and knowledge work together to deliver support at scale
• Create intelligent service operations that continuously learn, improve, and automate
• Own participant support, service operations, knowledge management, and operational excellence
• Work on one of Malaysia's most strategic Open Finance initiatives with significant visibility and impact

Why This Role Matters

• As Open Finance grows, participant operations cannot scale through additional manual effort alone.
• This role is responsible for designing and operating a new model where AI agents, structured knowledge, automation, and human expertise work together seamlessly to support participants and maintain operational excellence.
• You will help define how participant support is delivered, how knowledge is managed, how issues are resolved, and how operational processes become increasingly intelligent over time.
• This is not a traditional support or service desk role. It is a builder role focused on creating the future operating model for Open Finance participant operations.

This role ensures:

• Participants receive fast, consistent, and reliable support experiences
• Operational knowledge is structured, trusted, and accessible to both people and AI agents
• Service issues are identified, triaged, and resolved efficiently
• AI-enabled workflows are accurate, scalable, auditable, and properly governed
• Operations continuously improve through automation, intelligence, and data-driven insights

What You Will Actually Do

• Design and build the end-to-end AI-enabled participant operations model, including support workflows, service management processes, and operating procedures
• Create agentic workflows where specialised AI agents retrieve knowledge, analyse information, execute tasks, collaborate with other agents, and escalate to humans when necessary
• Own participant support operations, service desk performance, SLA monitoring, ticket management, and issue resolution processes
• Build and maintain the operational knowledge layer, including SOPs, playbooks, FAQs, troubleshooting guides, and self-service capabilities
• Develop AI-powered automation that reduces manual effort while improving service consistency, response times, and participant experience
• Analyse service trends, recurring issues, operational data, and automation effectiveness to identify continuous improvement opportunities
• Define controls and governance mechanisms that ensure AI-driven processes remain accurate, secure, traceable, and compliant
• Support participant onboarding, operational readiness exercises, go-live activities, hypercare periods, and ongoing production operations
• Partner closely with Product, Technology, Cybersecurity, Risk, Governance, and participants to ensure operational effectiveness and service excellence

Examples of This Role in Practice

• Designing an AI agent that automatically analyses incoming participant tickets, retrieves relevant knowledge, proposes solutions, and routes exceptions to the appropriate teams
• Creating a multi-agent workflow where specialised agents collaborate to diagnose operational issues before escalating to human operators
• Building a self-service support experience that enables participants to resolve common issues without submitting support tickets
• Identifying recurring support requests and converting them into automated workflows, reducing operational effort and improving response times
• Developing a knowledge repository that serves as the trusted source of information for both participants and AI agents
• Monitoring SLA breaches and service trends, then implementing automations that proactively prevent recurring operational issues
• Supporting a major Open Finance go-live by ensuring AI-enabled support processes remain operational, auditable, and properly governed during heightened activity periods

What Will Help You Succeed

• A builder mindset with the curiosity and resilience to create new capabilities from scratch
• Strong understanding of AI agents, agent orchestration, automation workflows, and how humans and AI collaborate effectively
• Ability to convert operational complexity into structured processes, knowledge, and scalable solutions
• Comfortable experimenting with emerging technologies and rapidly translating ideas into practical operational outcomes
• Strong analytical judgement and critical thinking, especially when evaluating AI outputs and identifying failure modes
• Ability to balance automation ambitions with operational risk, governance, and participant experience considerations
• Strong ownership and follow-through across support operations, process improvement, and stakeholder management
• Comfortable working in fast-evolving environments where solutions are often created rather than inherited

Helpful (Not Mandatory)

• Experience in payments, fintech, platform operations, or regulated financial services environments
• Exposure to Open Finance, Open Banking, APIs, developer ecosystems, or participant management models
• Experience designing agentic AI architectures involving agent orchestration, tool calling, RAG, specialised agents, and human-in-the-loop controls
• Hands-on experience with Microsoft Copilot Studio, Azure AI, OpenAI APIs, Power Automate, n8n, Make, or similar AI and automation platforms
• Experience supporting production operations, platform launches, hypercare, incident management, or service stabilisation activities
• Understanding of responsible AI principles, operational risk management, governance controls, and auditability requirements