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
