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

Senior Python Automation Test Engineer with AI