Senior Engineering Manager - Fraud

Get to Know the Team

GrabDefence is in the Integrity Group, building Grab's first B2B enterprise technology business. Through GrabDefence, we are opening up our fraud detection and prevention technology to our partners to help them battle fraud and fortify trust in the digital ecosystem.

GrabDefence is Grab's own Fraud detection and prevention technology platform for companies that want to protect themselves from fraudsters and fraudulent transactions. Drawing from Grab's own experience operating in multiple departments across the region and battling multiple fraud attempts, GrabDefence wants to help companies build Trust in their platforms. GrabDefence is consist of product lines such as AML, Chargeback protection, and eKYC solutions to its product portfolio, and all of these cutting-edge solutions based on AI will be launched this year, providing the applicant with a tremendous learning and growth opportunity.

This is your opportunity to be part of an exciting new team venturing into a new domain and be involved from strategy to execution. We are looking for driven, like-minded individuals who excel in an environment of rapid experimentation to join us!

Get to Know the Role

In this role, you will lead the backend engineering team responsible for strengthening and scaling Grab’s trust and fraud-protection capabilities. You will help build and modernize critical services that protect Grab’s users and businesses—including its digital banking operations—as well as external partners from fraud and evolving security threats.

You will combine people leadership with strong technical involvement. You will define the technical roadmap, drive architectural direction, lead system-design and code reviews, and work closely with engineers to resolve complex technical and production challenges. When needed, you may contribute directly to selected implementations, prototypes, or critical engineering initiatives.

You will bring a strong data-driven mindset to engineering and product decisions. You should be comfortable interpreting operational, product, and fraud-related data; identifying patterns and anomalies; validating assumptions; and using evidence to prioritize investments and measure outcomes. You should have sufficient analytical experience to ask the right questions, evaluate insights critically, and partner effectively with Data Science and Analytics teams.

You will be accountable for the reliability, security, scalability, and operational health of the services under your team’s ownership. Working with Product, Business, Data Science, Operations, Risk, and domain specialists, you will translate fraud-protection needs into robust backend capabilities and ensure that solutions deliver meaningful outcomes for internal teams and external partners.

You will also support the responsible adoption of AI-assisted engineering practices where they improve development quality, productivity, or operational effectiveness

The Critical Tasks You Will Perform

• Lead one or more backend engineering teams responsible for trust, fraud-prevention, and risk-related services.
• Translate business and product priorities into actionable technical roadmaps, delivery plans, and measurable engineering outcomes.
• Lead architecture and system-design reviews, ensuring solutions are scalable, secure, maintainable, resilient, and cost-efficient.
• Remain directly involved in technical execution by reviewing code, contributing targeted implementations or prototypes, and helping resolve complex production and engineering issues.
• Guide the uplift and modernization of existing services, addressing architectural limitations, technical debt, scalability constraints, and operational challenges.
• Improve engineering productivity and software delivery practices through automated testing, CI/CD, and reliable Jenkins build and deployment workflows.
• Own the operational health of business-critical backend services by strengthening observability, capacity planning, incident response, root-cause analysis, and preventative engineering.
• Drive the adoption of AI-assisted software-development practices and identify opportunities to apply AI to engineering workflows, platform capabilities, and fraud-prevention initiatives.
• Evaluate new technologies pragmatically and help teams move successful experiments into secure, maintainable, production-ready solutions.
• Collaborate with Product, Business, Data Science, Operations, Risk, and domain specialists to translate complex fraud-prevention requirements into reliable backend capabilities.
• Partner with Grab’s digital banking businesses, internal product teams, regional Trust teams, and external partners to understand their needs and deliver effective technical solutions.
• Foster a culture of ownership, psychological safety, technical rigor, collaboration, and continuous improvement.