Senior AI QA Engineer: Java + Python
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, semantic/graph, 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
