Fraud Risk AI Lead, Zalopay

About Zalopay Zalopay is one of Vietnam's leading digital payment platforms, serving millions of users across consumer payments, merchant acceptance, and financial services. Our fraud risk function is a small, high-trust team responsible for protecting the platform across account fraud, merchant risk, and promotion abuse, working closely with engineering, product, and business teams across the company.

About the Role We are looking for a Fraud Risk AI Lead to take our team into its next chapter. The team is analytically strong and fraud-domain-deep. What they need now is a leader who can build AI tools and agents that fundamentally change how the team operates, and systematically develop that same building capability across the team. This is a hands-on leadership role. You will build real things: investigation agents, monitoring automations, decision-support tools. You will also teach the team to build them. You will own fraud risk strategy across three domains (account risk, merchant risk, and promotion abuse), directly manage the team's data analyst, and lead the team's shift from manual operations to an AI-native way of working.

What You'll Do

• Build and deploy AI tools and agents: investigation brief generators, monitoring summary agents, alert triage tools, and rule optimisation assistants, using the Claude API, OpenAI/Codex, and/or Google AI Studio/Gemini API.
• Develop the team's AI building capability: run weekly building sessions, coach analysts to design and maintain their own domain-specific agents, and build a culture where AI is a normal part of daily work.
• Own fraud risk strategy across account risk, merchant risk, and promotion abuse, including rule design, detection coverage decisions, and risk-business tradeoff calls.
• Directly manage the data analyst, who is the data infrastructure partner for all AI tooling.
• Drive cross-functional coordination with engineering, product, business, loyalty, CRM/CS, and acquiring bank teams.
• Lead the operating rhythm: monthly reporting, quarterly strategic planning, and escalation decisions.

Must Have

• Fraud risk or trust and safety background: 4 to 6 or more years in fraud, payments risk, trust and safety, or a closely adjacent field. You understand false positive costs, fraud pattern logic, and the stakes of a wrong risk call from direct experience.
• Hands-on AI building experience: You have personally built and deployed a working tool or agent using an AI API (Claude, OpenAI/Codex, Google AI Studio/Gemini, or equivalent). We will ask for a demonstration during the interview process.
• Ability to teach: You can bring analytically-minded, non-engineering colleagues along on AI building. Patient, practical, and energised by teaching rather than doing alone.
• People management experience: Comfortable directly managing and developing at least one direct report.

Strong Advantage

• Experience with agent orchestration frameworks such as Anthropic Agent SDK, LangChain, or LlamaIndex
• Familiarity with payments fraud patterns: card fraud, velocity attacks, BIN exploitation, promotion abuse
• Experience with rule-based detection systems and precision/recall evaluation methodology
• Prior experience in a lean environment where you were simultaneously a hands-on practitioner and a team leader What This Role Is Not This is not a machine learning or data science role. Model development sits with a separate function. This is not a pure management role. You will remain a hands-on builder throughout. This is not a strategy-only role. Execution is core.

What You'll Find Here

• A lean, high-trust team with genuine fraud domain depth and strong analytical habits, ready to be transformed.
• Direct ownership: you set the AI tooling roadmap, make the risk strategy calls, and develop the team your way.
• Real technical surface area: Claude API, OpenAI, and Gemini API on problems that matter in a live, high-volume payment environment.
• A mandate to change how the team works, with leadership support and the space to do it properly.