AI-First Participant Operations Specialist

Fresher

Job Description

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