Job offer

Senior AI Test Automation Engineer

Julius Baer Bank is seeking a Senior AI Test Automation Engineer who will be responsible for the technical test automation solution of the AI and ML Ops platform and has experience in Python-based test automation and CI/CD pipelines. The candidate will be responsible for the architecture, implementation, and execution of test automation and will work closely with other teams.

Tasks

  • Define and further develop the technical test automation approach and test framework architecture for ML and AI-ART
  • Designing reusable, scalable test automation patterns (page objects, API clients, test data builders)
  • Analyzing and evaluating requirements, features, and user stories in terms of testability
  • Deriving test cases from technical and risk analyses of functional and non-functional requirements
  • Automating test cases using Python-based frameworks (Playwright/Python, requests + pytest, Behave, or pytest-bdd)
  • Designing and implementing A/ML-specific test cases (evaluation pipelines for LLM outputs)
  • Creating and maintaining contract tests (e.g., Pact) for platform APIs and microservice boundaries
  • Integrating and Orchestrating Automated Test Phases in GitLab CI/CD Pipelines
  • Planning, scheduling, and triggering automated test runs across environments
  • Monitoring execution health, investigating and quarantining flaky test cases, and maintaining a low false-positive rate
  • Prioritizing execution results, reporting errors in Jira with supporting evidence, and communicating quality signals
  • Generating execution evidence (run metadata, artifacts, reports) for audit and release governance

Requirements

  • Proven expertise in Python-based test automation (Playwright/Python, Behave, or pytest-bdd, requests + pytest)
  • Proven ability to design and maintain test automation frameworks, including reusable utilities and maintenance patterns
  • Practical experience with integrating and running automated tests in CI/CD pipelines
  • Experience with test execution, parameterization, flaky test management, and modern reporting tools (Allure, pytest-html, or equivalent)
  • Solid understanding of Git and version control workflows, ability to write clean code, and a culture of code review
  • Practical knowledge of Docker, familiarity with Kubernetes fundamentals (pods, namespaces)
  • Experience with AI/ML systems gained through testing, development, or applied projects is a strong plus; the ability to develop and demonstrate AI/ML testing expertise is essential
  • Fluency in English; Spanish is a plus

We offer

No information available.

Job details

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