Fraud & Risk Engineer

Who We Are

The world is moving towards instant digital payments and TabaPay 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. TabaPay is a highly profitable rocketship that processes billions of dollars each year. To learn more visit www.tabapay.com.

At TabaPay, 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 and 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 TabaPay 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.

Success in the first year looks like:

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.

What You’ll Do

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 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.

What We’re Looking For

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, DataVisor, Riskified or a comparable risk decisioning platform.
A systems thinker with the ability to see how one rule interacts with the rest
Proven proficiency with SQL and Python for advanced features
Proven proficiency with JSON data formats, APIs, REST, Git
Knowledge of fraud and financial crime typologies
Ability to build test cases and rule design workflows in the syntax of the risk tool(s)
Ability to translate ambiguous rule requests from a variety of stakeholders (technical and non-technical) and translate those requests into precise rule logic.

Preferred

Master’s Degree in a rigorous data discipline or mathematics
Experience within payments, fintech or financial services is a strong plus
Familiarity with BSA/AML requirements and typologies
Experience with AI-assisted rule design, testing, and iteration
Experience with Graph analytics, device intelligence, biometrics, experiment design
ML Modeling experience and/or training is a plus
Experience with business intelligence UIs is a plus
Familiarity with SDLC processes, release management and version control

We are ideally looking for people in the Bay Area who are available to come into our Palo Alto HQ 2-3 times a week.

The pay range for this position is $125,000; however, base pay offered may vary depending on job-related knowledge, skills, and experience. In addition to a full range of medical, financial, and/or other benefits, dependent on the position offered.

Benefits

TabaPay offers the following benefits:

100% employer-paid health care insurance including medical, dental, vision, and life insurance (for employee only)
Employer 401K Matching
Generous and Flexible PTO

EEO Employer: TabaPay is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.