Senior JavaScript Automation Test Engineer with AI & Agentic Testing

We're looking for aSenior JavaScript Automation Test Engineer to join the team, taking on a key part in guaranteeing software system reliability and accuracy, heading up a team of testers, overseeing automated testing processes, and helping to continuously enhance the test automation framework.

This role calls for someone who can build scalable automation solutions, champion quality engineering practices, guide and develop team members, and apply Generative AI and Agentic AI technologies to speed up software testing and delivery.

Responsibilities

• Guide and support a team of testers through their testing activities
• Work with cross-functional teams to collect and review system requirements
• Create thorough test plans, test cases, and test strategies
• Organize and prioritize testing tasks to achieve efficient, complete test coverage
• Build, develop, and run automation scripts using advanced automation tools
• Find, log, and monitor defects through to validation and resolution
• Establish and uphold quality standards in line with best practices
• Build and deploy API automation solutions for 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
• Set test strategies, automation roadmaps, and quality metrics
• Build AI-powered solutions for automated test case generation, test script creation, code reviews, and API-driven automation workflows

Requirements

• 5-8 years working in software test automation and quality engineering
• Strong skills in API test automation for REST and SOAP services, covering authentication methods like Basic Authentication, Bearer Tokens, OAuth, and NTLM
• Deep knowledge of software design patterns such as Singleton, Factory, Decorator, Page Object Model (POM), and Page Factory
• Experience integrating CI/CD and DevOps tools including Jenkins, GitHub Actions, and static code analysis tools
• Solid grasp of test strategy concepts such as Test Pyramid, Definition of Ready (DoR), and Definition of Done (DoD)
• Working knowledge of Confirmation Testing, Regression Testing, and Change Impact Testing
• Practical experience using Large Language Models like GitHub Copilot, Claude, and Cursor
• Familiarity with Prompt Engineering, Context Window Management, Tokenization, and Model Selection Strategies
• Experience with embeddings and vector databases for semantic search, similarity search, and retrieval tasks
• Ability to design AI-driven solutions using tools like Claude, GitHub Copilot, Cursor, and OpenAI Assistants
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field

Nice to have

• Experience creating multi-agent workflows for end-to-end testing, automated reporting, failure recovery, and fallback handling
• Familiarity with RAG architectures and connecting LLMs to enterprise knowledge sources
• Understanding of Model Context Protocol concepts and frameworks used to orchestrate agent interactions and monitor workflows
• Knowledge of Attention Mechanisms and Transformer-based model architectures