Senior AI QA Engineer: .NET + 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 capital market compliance platform aimed at streamlining compliance insights, rules, and workflows.

This role focuses on API, data, semantic/graph, and AI workflow validation.

You will work closely with backend 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 C#/.NET test automation
• Strong Python skills (5+ years experience)
• UI automation: Selenium / Playwright
• API automation: RestSharp / HttpClient
• 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)