Senior Automation Test Engineer

Job Description

• 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-Native Quality Engineering:

• 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.