Lead Java Automation Test Engineer with AI

We are looking for a Lead Java Automation Test Engineer with AI to shape scalable automation and AI-enabled quality practices. You will own Java/Selenium and API automation, guide architecture and standards, and integrate suites with Jenkins and GitHub Actions while applying Generative AI and Agentic AI approaches to speed delivery.

Responsibilities

• Design, develop, enhance, and maintain scalable Java-based test automation frameworks
• Build robust Selenium automation solutions for reliable coverage
• Drive framework architecture choices that improve scalability, maintainability, and reusability
• Implement parallel execution strategies and reduce run time across browsers and platforms
• Create reusable libraries, utilities, and framework extensions for teams
• Apply Object-Oriented Programming principles including classes and objects, inheritance, polymorphism, encapsulation, and abstraction
• Design and implement API automation solutions for REST and SOAP services
• Validate XML and JSON payloads using serialization and deserialization techniques
• Implement authentication and authorization mechanisms including Basic Authentication, Bearer Tokens, OAuth, and NTLM
• Manage sessions and execute API integration testing effectively
• Conduct code reviews and uphold clean coding standards
• Establish and govern coding standards, branching strategies, and version control best practices
• Integrate automation suites into CI/CD pipelines using Jenkins and GitHub Actions
• Design and implement AI-driven solutions for automated test case generation, test script generation, and code reviews

Requirements

• Extensive background in test automation engineering (9–14 years)
• Deep expertise in Java, Selenium, and test automation framework design
• Strong foundation in Object-Oriented Programming and design patterns such as Singleton, Factory, and Decorator
• Practical knowledge of Page Object Model and Page Factory
• Hands-on skills in API automation for REST and SOAP services, including XML and JSON validation
• Proven proficiency with CI/CD and DevOps integration using Jenkins and GitHub Actions
• Ability to set up static code analysis, quality gates, and automation reporting dashboards
• Direct experience with Large Language Models such as GitHub Copilot, Claude, and Cursor
• Working understanding of Prompt Engineering, Context Window Management, and Tokenization
• Familiarity with embeddings, vector databases, and semantic search use cases
• Exposure to AI agents and AI-assisted engineering with tools such as OpenAI Assistants

Nice to have

• Experience creating multi-agent and agentic workflows for end-to-end testing and workflow orchestration
• Knowledge of Retrieval-Augmented Generation architectures and integration with enterprise knowledge sources
• Understanding of Model Context Protocol concepts and frameworks
• Understanding of Attention Mechanisms and Transformer-based model architectures