About
We are looking for a QA Automation Engineer (Java) to join a team developing enterprise-grade, AI-powered applications. You will play a key role in establishing and maintaining automated quality assurance across backend services, APIs, frontend, and end-to-end user flows. The role also involves validating LLM-powered features through structured evaluation frameworks and integrating automated quality controls into CI/CD pipelines.
Relocation package
Job rotation
Learning through Arnia Academy
Attractive projects
Flexibile working hours
Performance bonuses
Medical benefits
Trainings
Competitive compensation package
Referral program
International work experience

Requirements

  • 3+ years of experience in QA Automation for production environments
  • Strong experience testing Java backend applications, preferably built with Spring/Spring Boot
  • Solid hands-on experience with frontend test automation
  • Experience building and maintaining end-to-end test suites using Playwright, Cypress, or Selenium
  • Strong API testing experience, including REST services, schema validation, authentication, and error handling scenarios
  • Experience working with SQL databases, preferably PostgreSQL, and managing test data
  • Experience integrating automated testing into CI/CD pipelines using GitHub Actions, Azure Pipelines, or Jenkins
  • Practical understanding of testing AI/LLM-powered applications and validating non-deterministic outputs
  • Familiarity with Agile development methodologies and collaborative engineering practices
  • Strong analytical, troubleshooting, and communication skills

 

Responsibilities

  • Design, develop, and maintain automated API, integration, frontend, and end-to-end test suites for Java-based applications
  • Build comprehensive test coverage for backend services, database workflows, and critical user journeys
  • Implement reliable mocking strategies and reusable test fixtures to support stable automated testing
  • Configure and maintain CI/CD quality gates covering linting, automated testing, code coverage, and reporting
  • Expand automated test coverage across new features while proactively preventing regressions
  • Establish evaluation frameworks for LLM-powered functionality using golden datasets and measurable quality metrics
  • Monitor AI model behavior, identify output drift, and support release decisions through automated quality validation
  • Improve test reliability by reducing flakiness and optimizing execution time
  • Collaborate closely with developers to promote quality-first engineering practices throughout the software development lifecycle
  • Contribute to continuous improvement of testing frameworks, automation processes, and engineering standards

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General application

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