The opportunity
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
What you'll do
You will own and deliver quarterly goals for your team, leading engineers: through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery.
You will design and implement real-time fraud decisioning services and APIs: in Python or Kotlin, extending Affirm's Fraud Decisioning System to markets beyond the US.
You will build and evolve the platform and tooling that let Affirm launch: fraud decisioning in a new country quickly—turning market-by-market setup (rules, models, and vendor configuration) into a repeatable, low-friction path so launches scale sub-linearly with the number of markets.
You will integrate region-specific fraud and risk vendors and help: operationalize the machine learning and AI signals that power real-time decisioning, while using modern AI tooling to move faster as an engineer.
You will support peers and stakeholders across the product development: lifecycle - collaborating with Product, Machine Learning, Analytics, and Fraud Strategy, articulating technical constraints, and partnering on decisions that properly weigh risks and trade-offs.
You will support the operations and availability of your team's systems by: creating and monitoring metrics, escalating when needed, and contributing to keep-the-lights-on and on-call efforts.
What they're looking for
- You will foster a culture of quality and ownership: setting and improving code review and design standards, mentoring teammates, and leading by example.
- + years of experience building backend systems at scale using Python or Kotlin.
- Experience with distributed systems and infrastructure using AWS, MySQL/PostgreSQL, and Kubernetes.
- Strong system design skills and a track record of delivering maintainable, extensible services.
