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.

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.

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.

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.

Job description provided by Foodhub.
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