Senior Software Engineer

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. The Fraud Engineering organization builds the foundational and tactical software that enables Affirm to respond strategically to fraud - both in real time and after the transaction. Our mission is to support business growth while protecting Affirm, our buyers, and our merchants. We evaluate risk at critical decision points in the user journey, rapidly adapt to evolving fraud patterns, and equip operations teams with the tools needed to investigate and mitigate fraud at scale. We’re looking for a Senior Software Engineer to join our fully remote team based in Europe. You’ll collaborate closely with stakeholders across North America - including teams in Product, Compliance, Machine Learning, Fraud Operations, Fraud Strategy, and other Fraud Engineering teams. The Fraud Engineering organization builds the foundational and tactical software that enables Affirm to respond strategically to fraud - both in real time and after the transaction. Our mission is to support business growth while protecting Affirm, our customers, and our merchants. We evaluate risk at critical decision points in the user journey, rapidly adapt to evolving fraud patterns, and equip operations teams with the tools needed to investigate and mitigate fraud at scale. The Fraud International Team (FIT) leads the engineering effort to extend Affirm's Fraud Decisioning System into markets beyond the US - Canada, the UK, Australia, and growing rapidly. We own real-time fraud decisioning for these markets, integrate region-specific risk vendors, and are building the platform that lets Affirm stand up fraud protection in a new country quickly and safely. As Affirm expands globally, FIT scales with it. We're looking for a Senior Software Engineer to join our fully remote team based in Europe. You'll collaborate closely with stakeholders across North America - including teams in Product, Compliance, Machine Learning, Fraud Operations, Fraud Strategy, and other Fraud Engineering teams. What You'll DoYou 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. You will foster a culture of quality and ownership - setting and improving code review and design standards, mentoring teammates, and leading by example. What We Look For5+ 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. Fluency with AI-driven engineering - every Affirm engineer builds with tools like Claude Code and most PRs are co-authored with AI, so directing and orchestrating AI and excelling in the reviewer's seat (setting intent, critically evaluating generated code, and owning its correctness, quality, and security) is a core expectation. Proficiency in SQL and working with data-rich environments. Familiarity with CI/CD practices and safe production deployments. Strong written and verbal communication skills, especially in distributed teams. A proactive, ownership-driven mindset with a focus on learning and team success. Experience with Snowflake, dbt, Airflow, or Chronosphere (nice to have)Background in fraud prevention, risk systems, or real-time decisioning (nice to have)Experience building for multiple markets or regions - internationalization or localization (nice to have)Experience working in the fintech sector or other highly regulated environments, with a strong understanding of risk, compliance, and operational constraints. (nice to have)Compensation & BenefitsBase Pay Grade - NEquity Grade - 4Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). POL base pay range per year: 308,000 zł - 428,000 zł Additional benefits include: Flexible Spending Wallets for tech, food and lifestyleAway Days - wellness days to take off work and rechargeLearning & Development programsParental benefitsEmployee Resource & Community GroupsThis role is eligible for creative tax benefits, subject to applicable law and company policyLocation - Remote PolandThe majority of our roles can be located anywhere in Poland. This job description is not a contractual document and is not intended to have binding force.