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SEON is a fraud prevention and AML compliance platform serving thousands of companies globally. The company uses 900+ real-time data signals to enrich customer profiles, flag suspicious behavior, and streamline compliance workflows. SEON has helped clients reduce fraud by 95% and achieve 32x ROI, with partnerships including Revolut, Wise, and Bilt.
You will own end-to-end quality outcomes for SEON's core Scoring engine as a hands-on Test Engineer and full contributor. This role operates within an AI-native quality model where defect prevention begins upstream before code is written. Manual testing is intentionally minimized; your primary focus will be high-leverage test engineering and evolving the quality harness.
You will not simply follow existing frameworks—you are expected to augment them by building new methodologies from scratch when necessary, while teaching and improving these patterns for team-wide benefit. You will participate in owning the quality architecture for the Scoring engine, prioritizing test strategies based on real-world risk and standardizing reusable patterns. You will build reliable automated coverage across UI, API, and deep service layers using BMAD and TeA shift-left methodologies.
You will operate as a power user of AI-first IDEs, integrating specialized agents into your daily workflow to rapidly scale test coverage for unit, integration, and component layers. During PR reviews, you will act as an AI-First Test Engineer, enforcing quality gates and identifying boundary violations and edge cases that AI coding agents may have missed. You will implement integration, k6 performance smoke tests, and Pact contract testing directly into CI/CD pipelines to block cross-service regressions before they merge.
You will proactively track new AI testing tools and capabilities, sharing relevant findings and advanced prompting strategies with the team to improve overall engineering velocity. You will represent system health in feature discussions, clearly explaining tradeoffs and maintaining high documentation standards with exemplary PR descriptions and context-rich technical inputs.
The role is based in the Budapest office on a hybrid schedule.
REQUIREMENTS:
- 3+ years of QA automation experience with deep knowledge of REST APIs and event-driven systems
- Hands-on coding expertise in Java and test automation experience using Playwright and TypeScript (strictly required)
- Demonstrable experience using AI-driven development or test generation methodologies to scale automation coverage
- Proven ability to treat AI-generated output as a starting point, applying rigorous engineering judgment to independently identify and correct logic errors or hallucinations in test code
- Proven ability to build and manage automated merge gates in CI/CD pipelines like GitHub Actions
- Confident communication skills to represent system health in feature discussions, clearly explaining tradeoffs
- High documentation standards with exemplary PR descriptions and context-rich technical inputs
NICE TO HAVE:
- Direct experience with BMAD (Breakthrough Method for Agile AI-Driven Development) framework
- Experience with service virtualization (WireMock) or Pact contract testing
