We are seeking a Lead Python Automation Test Engineer with AI expertise to design scalable automation solutions, drive quality engineering practices and leverage Generative AI and Agentic AI technologies to accelerate software testing and delivery. This role requires strong technical leadership, framework architecture expertise and experience driving enterprise-wide automation initiatives.
Responsibilities
Design, develop and maintain scalable test automation frameworks using Python
Build automation solutions using PyTest, Behave, Robot Framework, Selenium and Playwright
Lead framework architecture decisions focused on scalability, maintainability and reusability
Implement parallel execution strategies to optimize execution times across browsers and platforms
Develop reusable libraries, utilities and framework extensions
Design and implement 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
Mentor team members on Python, automation frameworks and quality engineering practices
Lead technical discussions and guide teams toward automation excellence
Requirements
9 to 12 years of experience in test automation engineering with strong Python expertise
Expertise in PyTest, Behave, Robot Framework, Selenium and Playwright
Knowledge of Object-Oriented Programming principles and advanced Python concepts such as decorators, iterators and exception handling
Proficiency in API test automation for REST and SOAP services including authentication mechanisms like OAuth, Bearer Tokens and NTLM
Familiarity with software design patterns including Singleton, Factory and Page Object Model
Experience integrating automation suites with CI/CD pipelines using Jenkins and GitHub Actions
Understanding of Test Pyramid principles, shift-left testing practices and quality metrics
Hands-on experience with LLMs such as GitHub Copilot, Claude and Cursor
Understanding of prompt engineering, context window management and tokenization
Experience generating and utilizing embeddings for semantic search applications
Background in designing AI-driven solutions for test automation workflows
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering or related field
Nice to have
Understanding of Attention Mechanisms and Transformer-based model architectures
Capability to evaluate and optimize model performance and focus
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