We're hiring a QA Automation Engineer (5 to 10 years of experience) to drive automation-first, AI-assisted testing across our backend platform. You'll spend most of your time building Playwright suites, designing AI agents, and shaping what quality looks like in an agent-driven SDLC — with manual testing reserved only for exploratory and edge cases automation can't yet reach.

Responsibilities:

● Build and own automated test suites using Playwright for end-to-end, UI, and API testing across backend services and platform workflows.

● Use Claude Code (agents, skills, MCP servers) as a daily driver — generating test cases, test data, and edge-case scenarios from requirements, PRs, and production signals — shrinking test authoring time from days to hours.

● Design AI agents that own slices of the SDLC — from PR-triggered test design to autonomous regression triage and release sign-off.

● Build custom Claude skills and MCP servers that integrate QA workflows with Jira, CI/CD pipelines, test data stores, ScyllaDB/Kafka inspection tools, and observability platforms.

● Apply AI-driven defect prediction, root cause analysis, and flaky test detection to focus effort where it matters most.

● Embed automated quality gates into CI/CD (GitHub Actions) — including AI-powered code review, test impact analysis, and regression triggers — to shift quality left.

● Validate datasets using SQL across transactional and analytical systems.

Requirements:





● 5+ years in QA with a clear bias toward automation and tooling over manual execution, and a track record of measurably reducing manual effort or escape defects.

● Strong hands-on experience with Playwright (or equivalent modern framework — Cypress, Selenium) for UI and API automation, including Page Object Model and TestNG (or similar) framework design.

● Proficiency in Java, JavaScript/TypeScript, or Python, with solid API testing skills using Postman/Insomnia.

● Solid SQL for data validation, plus working knowledge of NoSQL databases (MongoDB, ScyllaDB, or DynamoDB).

● Working understanding of API/backend test lifecycles and exposure to the AWS cloud platform.

● CI/CD experience with GitHub Actions, Jenkins, or equivalent.

● Working fluency in LLM-powered development workflows (Claude Code, Cursor, Copilot, or similar) for test generation, debugging, and review.

● Grasp of AI/ML fundamentals — prompt engineering, context management, and evaluating LLM outputs for correctness and reliability.

● Agile/Scrum experience and clear async communication for remote, cross-functional work.

Nice to Have

● Built MCP servers or custom Claude skills/tools to extend AI agent capabilities.

● Exposure to agentic test orchestration — autonomous agents that plan, execute, and adapt test runs based on code or requirement changes.

● Experience measuring AI-assisted productivity metrics (test creation velocity, coverage uplift, defect escape rate).

📌 QA Automation Engineer (India)
🏢 Cube Consultancy Services
📍 India