Senior Automation Test Engineer

• 5–8 years in software testing, SDET or Quality Engineering, with strong hands-on automation experience.

• Strong programming skills in Java, TypeScript or JavaScript.
• Strong Playwright experience and automation framework design experience.
• Strong API automation experience; REST Assured or equivalent.
• CI/CD, Git, debugging and strong software-testing fundamentals.
• Functional, integration, regression and end-to-end testing.
• Appium/mobile automation experience is strongly preferred.
• Selenium, TestNG/JUnit, SQL, Docker/cloud execution, performance or security testing are valuable.

Requirements

• AI is a core requirement of this role. You will use AI throughout the quality lifecycle—not simply as an occasional chatbot.
• Analyze requirements and acceptance criteria; identify missing scenarios, edge cases and risks.
• Generate and improve test scenarios, automation code and synthetic test data.
• Use AI coding assistants to accelerate development, refactoring, debugging and test maintenance.
• Use AI to analyze failed tests, logs, screenshots and stack traces and accelerate root-cause analysis.
• Explore AI-assisted test maintenance, intelligent regression selection and self-healing approaches.
• Automate QA reporting and test-result analysis where practical. Automation & Continuous Testing:
• Build scalable automation using Playwright and appropriate supporting technologies.
• Develop API automation and validation; use API-level tests to reduce unnecessary UI testing.
• Maintain functional, integration, regression and end-to-end automation.
• Use Appium for mobile automation where required; Selenium experience is valuable.
• Reduce flaky tests, enable parallel execution and improve feedback time.
• Integrate automation into Jenkins or equivalent CI/CD pipelines and establish meaningful quality gates.
• Continuously identify manual testing that can be automated or eliminated. AI / LLM Quality
• Test AI features for accuracy, relevance, consistency, reliability, context handling and failure behavior.
• Evaluate hallucinations, prompt injection, adversarial inputs, safety/guardrails and boundary conditions.
• Define evaluation criteria and automated evaluation pipelines for AI-powered features.
• Experience with RAG, embedding, vector databases, conversational AI, tool/function calling or AI agents is strongly preferred.
• Understand testing of the full RAG flow: Query → Retrieval → Context → LLM → Response.
• Understand agent risks such as incorrect tool selection, invalid parameters, repeated calls, state errors and failure recovery. Quality Engineering & Product Ownership
• Challenge unclear requirements and implementations constructively.
• Work closely with developers and product managers to identify quality risks early.
• Participate in refinement, sprint planning, design discussions, release planning and retrospectives.
• Investigate defects rather than simply reporting them; think from the customer perspective.
• Balance release speed with product quality in a fast-moving Agile environment.