Test Engineer

SEON is the command center for fraud prevention and AML compliance, helping thousands of companies worldwide stop fraud, reduce risk and protect revenue. Powered by 900+ real-time, first-party data signals, SEON enriches customer profiles, flags suspicious behavior and streamlines compliance workflows - all from one place. SEON provides richer data, more flexible and transparent analysis, and faster time to value than any other provider on the market. We’ve helped companies reduce fraud by 95% and achieve 32x ROI, and we’re growing fast, thanks to our partnerships with some of the world’s most ambitious digital brands like Revolut, Wise, and Bilt.

We are looking for a hands-on Test Engineer to own end-to-end quality outcomes for SEON's core Scoring engine. At this level, you are a full contributor who owns outcomes and operates as the undisputed technical expert for your feature areas. We are actively executing an AI-native quality model where defect prevention starts upstream before code is even written. As manual testing is intentionally minimized, your primary focus will be on high-leverage test engineering and evolving our quality harness. You will not just follow the existing framework, you will be expected to augment it by building new methodologies from scratch when necessary, while teaching and improving these patterns for team-wide benefit.

This role strictly requires strong coding experience in both Java and Playwright with TypeScript, as well as proven experience with AI-driven test generation.

This role is based in our Budapest office on a hybrid schedule.

WHAT YOU’LL DO:

• Participate in owning the quality architecture for the Scoring engine, prioritizing test strategies based on real-world risk and standardizing reusable patterns for the repository
• Build reliable automated coverage across our UI, API, and deep service layers, driven fundamentally by our BMAD and TeA shift-left methodologies
• 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
• Using BMAD-TeA, act as an AI-First Test Engineer during PR reviews to enforce quality gates, identifying boundary violations and edge cases that AI coding agents failed to anticipate
• Implement integration, k6 performance smoke tests, and Pact contract testing directly into CI/CD pipelines to block cross-service regressions before they merge
• Proactively track new AI testing tools and capabilities, sharing relevant findings and advanced prompting strategies with the team to improve overall engineering velocity

WHAT YOU’ll BRING:

• 3+ years of QA automation experience with deep knowledge of REST APIs and event-driven systems
• Hands-on coding expertise in Java, alongside test automation experience using Playwright and TypeScript
• 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
• A confident voice that represents system health in feature discussions, clearly explaining tradeoffs without turning it into a battle of opinions
• High documentation standards, consistently producing exemplary PR descriptions and context-rich technical inputs that serve as a baseline for the team

(AMAZING IF YOU ALSO HAVE):

• Direct experience working within the BMAD (Breakthrough Method for Agile AI-Driven Development) framework
• Experience with service virtualization (WireMock) or Pact contract testing

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