Senior JavaScript Automation Test Engineer with AI & Agentic Testing

We're looking for a Senior JavaScript Automation Test Engineer to join our team. In this role, you'll help guarantee the accuracy and dependability of our software systems, lead a team of testers, oversee automated testing processes, and help improve our test automation framework on an ongoing basis.

The successful candidate will design scalable automation solutions, champion quality engineering practices, mentor team members, and apply Generative AI and Agentic AI technologies to speed up software testing and delivery.

Responsibilities

• Guide and mentor a team of testers, offering support throughout testing activities
• Work with cross-functional teams to collect and review system requirements
• Create detailed test plans, test cases, and test strategies
• Organize and prioritize testing tasks to achieve thorough and efficient coverage
• Build and run automation scripts using advanced automation tools
• Track, report, and follow up on defects to ensure proper validation and resolution
• Establish and uphold quality standards that reflect best practices
• Build 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
• Develop test strategies, automation roadmaps, and quality metrics
• Create AI-powered solutions for generating test cases, writing test scripts, reviewing code, and automating API-driven 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, including Singleton, Factory, Decorator, Page Object Model (POM), and Page Factory
• Experience integrating CI/CD and DevOps tools such as Jenkins, GitHub Actions, and static code analysis tools
• Solid grasp of test strategy concepts, including Test Pyramid, Definition of Ready (DoR), and Definition of Done (DoD)
• Working knowledge of Confirmation Testing, Regression Testing, and Change Impact Testing
• Practical experience with Large Language Models like GitHub Copilot, Claude, and Cursor
• Solid understanding of 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
• A Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline

Nice to have

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