Fraud & Risk Engineer

Who We Are

The world is moving towards instant digital payments and Taba Pay is leading the way. We help thousands of Fintechs in the US and Canada instantly move money in and out of accounts and we are actively expanding into other countries. Our customers represent the hottest verticals in the financial service industry such as neobanks, challenger brokers, gaming and wallets. Taba Pay is a highly profitable rocketship that processes billions of dollars each year.

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At Taba Pay, delivering best-in-class financial crime prevention is central to our mission. We’re building the next generation of scalable, configurable risk decisioning capabilities, and we’re looking for a Fraud & Risk Decisioning Engineer to help drive that effort.

In this highly hands‑on individual contributor role, you’ll design, build, test, deploy, monitor, and optimize fraud detection and risk decisioning rules that transform fraud trends, analyst insights, client needs, and regulatory requirements into high‑impact solutions. You’ll own the full lifecycle of decisioning logic while helping establish the standards, processes, and engineering practices that will scale Taba Pay’s Risk Platform.

This foundational, high‑visibility role sits at the intersection of fraud strategy and technical execution. You’ll partner closely with Financial Crimes Compliance, Fraud Risk, Chargebacks, Product, Engineering, Operations, Client Services, and Insights to strengthen our real-time fraud and financial crime detection capabilities. We are looking for a builder, investigator, analyst, and technical problem solver who is passionate about creating intelligent risk solutions.

• Deliver a portfolio of high-quality production decisioning rules.
• Establish repeatable standards for rule design, testing and documentation.
• Improve rule quality and deployment velocity through reusable templates and engineering best practices.
• Build the foundation for a scalable decisioning engineering practice.

• Assume ownership of all fraud and risk monitoring and blocking rules within our risk monitoring tool(s) across all use cases.
• Partner with Risk Product, Insights, Fraud Operations and Financial Crimes Compliance to define requirements for high impact rules that serve both clients and internal stakeholders as customers.
• Create rule packages: precise decision logic, assumptions, test cases, acceptance criteria, documentation and performance monitoring plans.
• Design decision architecture and build reusable decision frameworks.
• Design configurable rule templates that enable clients and internal users to safely manage decisioning through self‑service capabilities
• Perform rigorous validation before shipping rules for deployment
• Work closely with our Insights team to test rule efficacy – do the rules combat fraud, control for false positives, and deliver measurable value for our customers.
• Craft precise risk decisioning workflows for all individual rules as well as the decision tree designs across use cases and the company level portfolio view.
• Leverage AI‑assisted development tools to accelerate rule design, documentation, testing, validation and ongoing optimization
• Evaluate emerging AI techniques for fraud rule generation, simulation and decision explainability.
• Apply engineering discipline to rule authorship – versioning, testing, modularity, documentation.
• Present to stakeholders why the rule exists, how it works, how it fits within the risk strategy and the expected customer impact
• Drive rule experimentation through A/B testing, shadow mode assessments and phased rollouts in production
• Staying current. You keep pace with the fraud monitoring and decisioning tooling landscape (rules engines, feature stores, decisioning platforms, emerging typologies) and bring ideas home.

• Bachelor’s Degree in Computer Science, Systems Engineering, Mathematics or similar
• 4+ years of work in fraud strategy, risk rule design or decisioning
• Must have hands‑on experience authoring, configuring and tuning rules in a decisioning or rules engine such as Featurespace, Feedzai, Data Visor, Riskified or a comparable…