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Luxoft

Senior AI QA Engineer: Java + Python

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Project description

We are looking for a Senior Automation QA Engineer who will design and implement a complete automated testing framework for a complex, data heavy, AI enabled market data analytics platform. This role focuses on API, data and AI workflow validation. You will work closely with backend and frontend engineers, data engineers, and ML teams to build a robust automated quality layer across all components of the platform.

Responsibilities

  • Manual Testing
  • Analyze requirements, acceptance criteria, and specifications for new features.
  • Create and maintain test plans, test cases, and test scenarios across UI, API, and data workflows.
  • Perform functional, regression, exploratory, and integration testing.
  • Validate correctness of data transformation, analytical workflows, and large dataset processing.
  • Collaborate closely with Product, Developers, and Data/AI Engineers to clarify expected behavior. Automation
  • Develop and maintain UI automation using Selenium.
  • Implement E2E scenarios covering cross-service workflows.
  • Integrate tests into CI/CD pipelines (GitHub Actions / GitLab / Jenkins / AWS CodeBuild).
  • Configure test runs in AWS environments (dev/stage).
  • Participate in root-cause analysis of defects and quality incidents. Quality Engineering
  • Contribute to QA strategy and test automation roadmap.
  • Improve test stability, reduce flakiness, optimize runtime.
  • Define KPIs for coverage, quality, and regression scope.
  • Support test data preparation and environment setup.

SKILLS

Must have

  • Strong experience (8+ years) in Java test automation
  • UI automation: Selenium
  • API automation: RestSharp / HttpClient / Postman
  • SQL proficiency
  • Experience testing data pipelines (ETL/ELT)
  • RAG/LLM QA experience (prompt testing, embeddings validation)
  • CI/CD pipeline automation (Docker, GitHub Actions/GitLab/Azure DevOps)
  • Solid understanding of testing methodologies, QA lifecycle, and Agile processes.
  • Ability to analyze complex workflows and large datasets.
  • Strong communication skills and a proactive mindset.

Nice to have

• Experience with Capital Markets, trading, market data, or financial analytics. • Strong Python skills (5+ years experience) • LangChain familiarity • Performance testing (Locust/k6) • Experience with ontologies / RDF / semantic data modeling • Infrastructure as Code understanding (Terraform/CloudFormation basics) • Experience with Graph Databases (Graph DB, SPARQL or Cypher) • SHACL validation experience