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:

o Selenium

o Playwright

• 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.

Mandatory Skills Description:

• Strong experience (5+ years) in Java test automation

• Strong Python skills (5+ years experience)

• UI automation: Selenium

• API automation: RestSharp / HttpClient / Postman

• Experience with Graph Databases (Graph DB, SPARQL or Cypher)

• SHACL validation experience

• SQL proficiency

• Experience testing data lakehouse tech (Iceberg)

• 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 Skills Description:

• Experience with Capital Markets, trading, market data, or financial analytics.

• LangChain familiarity

• Performance testing (Locust/k6)

• Experience with ontologies / RDF / semantic data modeling

• Infrastructure as Code understanding (Terraform/CloudFormation basics)