Senior Python Automation Test Engineer with AI
We are seeking a Senior Python Automation Test Engineer with AI to design scalable automation frameworks, drive quality engineering practices and leverage Generative AI and Agentic AI technologies to accelerate software testing and delivery. The ideal candidate will demonstrate strong technical leadership, framework architecture expertise and experience driving enterprise-wide automation initiatives.
Responsibilities
- Design, develop, enhance and maintain scalable test automation frameworks using Python
- Build robust automation solutions using PyTest, Behave, Robot Framework, Selenium and Playwright
- Lead framework architecture decisions focused on scalability, maintainability and reusability
- Implement parallel execution strategies and optimize execution times across browsers and platforms
- Establish API automation solutions for REST and SOAP services
- Validate XML and JSON payloads through serialization and deserialization techniques
- Conduct code reviews and enforce clean coding standards
- Integrate automation suites with CI/CD pipelines using Jenkins and GitHub Actions
- Define test strategies, automation roadmaps and quality metrics
- Collaborate with QA, Development, Product and Business teams
- Mentor team members on Python, automation frameworks, design patterns and quality engineering practices
- Apply AI-driven solutions for automated test case generation, test script generation and code reviews
Requirements
- 5-9 years of experience in test automation engineering
- Proficiency in Python including Object-Oriented Programming principles, decorators and exception handling
- Expertise in PyTest, Behave and Robot Framework combined with Selenium and Playwright
- Skills in API testing including authentication mechanisms such as Basic Authentication, Bearer Tokens and OAuth
- Knowledge of software design patterns including Singleton, Factory and Page Object Model
- Familiarity with CI/CD tools such as Jenkins and GitHub Actions including static code analysis and quality gates
- Understanding of Test Pyramid principles, Definition of Ready and Definition of Done
- Hands-on experience with LLMs such as GitHub Copilot, Claude and Cursor
- Understanding of Prompt Engineering, Context Window Management and Tokenization
- Skills in generating and utilizing embeddings for semantic search applications including similarity search and retrieval mechanisms
- Background in designing AI-driven solutions using tools such as Claude, GitHub Copilot and Cursor
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering or related field
Nice to have
- Knowledge of RAG architectures and experience integrating LLMs with enterprise knowledge sources
- Understanding of Model Context Protocol concepts and ability to orchestrate agent interactions and task delegation
- Understanding of Attention Mechanisms and Transformer-based model architectures
- Capability to build multi-agent workflows for end-to-end testing, automated reporting and failure recovery
