Lead JavaScript Automation Test Engineer with AI & Agentic Testing

Lead JavaScript Automation Test Engineer

Responsibilities

• Lead and mentor a team of testers, offering direction and support throughout testing activities
• Work with cross-functional teams to collect and evaluate system requirements
• Create detailed test plans, test cases, and testing strategies
• Organize and prioritize testing tasks to achieve efficient and comprehensive coverage
• Build, develop, and run automation scripts using advanced testing tools
• Report and track defects, ensuring they are properly validated and resolved
• Establish and uphold quality standards in line with best practices
• Build and implement API automation solutions for both REST and SOAP services
• Verify XML and JSON payloads using serialization and deserialization methods
• Connect automation suites to CI/CD pipelines through Jenkins and GitHub Actions
• Lead in-sprint automation efforts, shift-left testing approaches, and Test Pyramid strategies
• Guide team members on automation frameworks, design patterns, and quality engineering techniques

Requirements

• 9 to 14 years of experience in test automation and quality engineering
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline
• Strong knowledge of authentication and authorization methods, including Basic Authentication, Bearer Tokens, OAuth, and NTLM
• Familiarity with software design patterns such as Singleton, Factory, Decorator, Page Object Model (POM), and Page Factory
• Experience setting coding standards, branching strategies, and version control best practices
• Ability to configure static code analysis, quality gates, and automation reporting dashboards
• Understanding of Definition of Ready (DoR), Definition of Done (DoD), Confirmation Testing, Regression Testing, and Change Impact Testing
• Practical experience with LLMs including GitHub Copilot, Claude, and Cursor
• Knowledge of Prompt Engineering, Context Window Management, Tokenization, and Model Selection Strategies
• Experience creating and applying embeddings for semantic search use cases, such as similarity search and retrieval
• Skill in designing AI-powered solutions for automated test case and script generation, code reviews, linting checks, and API-based automation workflows using tools like Claude, GitHub Copilot, Cursor, and OpenAI Assistants

Nice to have

• Experience developing multi-agent workflows and collaborative agent systems for End-to-End Testing, Automated Reporting, Failure Recovery, Fallback Handling, and Workflow Orchestration
• Familiarity with RAG architectures and integrating LLMs with enterprise knowledge sources
• Knowledge of Model Context Protocol concepts and frameworks, including orchestrating agent interactions, task delegation, and workflow monitoring
• Awareness of Attention Mechanisms and Transformer-based model architectures