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Senior AI QA Engineer: .NET + Python(Only short NP-less than 30 days accepted, kindly pay attention to this to save your efforts, thank you for understanding)

Luxoft India

5 - 10 years

Hyderabad

Posted: 07/03/2026

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Job Description

About the job

Attention please

Only short NP-less than 30 days accepted, kindly pay attention to this to save your efforts, thank you for understanding


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.

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