Senior Python Automation Test Engineer with AI

Role overview

Responsibilities

• Design, develop, enhance, and maintain scalable Python test automation frameworks.
• Build solutions with PyTest, Behave, Robot Framework, Selenium, and Playwright; lead architecture for scalability, maintainability, and reuse.
• Implement parallel execution and optimize execution times across browsers and platforms.
• Automate REST and SOAP APIs; validate XML and JSON payloads through serialization and deserialization.
• Conduct code reviews and enforce clean coding standards; integrate suites with Jenkins and GitHub Actions CI/CD pipelines.
• Define test strategies, automation roadmaps, and quality metrics; collaborate with QA, Development, Product, and Business teams.
• Mentor team members in Python, frameworks, design patterns, and quality engineering.
• Apply AI-driven solutions for automated test-case and script generation and code reviews.

Required qualifications

• 5–9 years of test automation engineering experience.
• Proficiency in Python, including object-oriented programming, decorators, and exception handling.
• Expertise in PyTest, Behave, and Robot Framework combined with Selenium and Playwright.
• API testing skills including Basic Authentication, Bearer Tokens, and OAuth.
• Knowledge of Singleton, Factory, and Page Object Model design patterns.
• Familiarity with Jenkins and GitHub Actions CI/CD, static code analysis, and quality gates.
• Understanding of Test Pyramid principles, Definition of Ready, and Definition of Done.
• Hands-on LLM experience with GitHub Copilot, Claude, and Cursor; understanding of prompt engineering, context windows, and tokenization.
• Experience generating and using embeddings for semantic search, similarity search, and retrieval.
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Nice-to-have qualifications

• Knowledge of RAG architectures and integrating LLMs with enterprise knowledge sources.
• Understanding of Model Context Protocol concepts and agent interaction and task delegation.
• Understanding of attention mechanisms and Transformer-based model architectures.
• Ability to build multi-agent workflows for end-to-end testing, automated reporting, and failure recovery.

Benefits and development

• Offers learning and self-development opportunities, online university resources, external certifications, and international knowledge sharing.
• Includes sponsored tech talks and hackathons, LinkedIn Learning, and individual development.
• Benefit package includes health, retirement, paid time off, and flexible benefits.
• Offers possible relocation to an EPAM office for short- or long-term projects and forums for interests beyond work.