Описание

We are growing and looking to hire a QA Automation Engineer who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity. Claroty is a global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. We’re a fast-growing, award-winning team where innovation meets purpose—and we want you to help us define the future of cybersecurity. At Claroty, our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all Claroty products, delivering deep visibility across CPS environments—without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments.

Responsibilities

Architect and expand reliable API and UI automation frameworks to drive comprehensive test coverage and minimize release risk
Embed automated quality gates directly into CI/CD pipelines, accelerating feedback loops and enabling seamless continuous integration
Lead deep root-cause analysis on complex automation and system failures, driving long-term stability and product resilience
Partner across Engineering, Product, and QA to align testing scope, elevate software quality standards, and ensure release readiness
Integrate modern AI solutions into day-to-day workflows to improve operational output, speed, and efficiency

Requirements

Minimum of 4+ years of hands-on experience in software QA methodology and test automation development
Deep proficiency in API and UI automated testing frameworks (e.g., Playwright, Selenium, or BE tools) with web application testing experience
Strong programming fundamentals with hands-on experience in Python (Big advantage)
Demonstrated experience with version control systems (Git) and CI/CD pipelines (e.g., Jenkins)
Solid problem-solving mindset with the ability to tackle unstructured technical problems and execute end-to-end QA lifecycle strategies
Practical experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, LLMs) to optimize testing workflows and code quality
Familiarity with Linux environments, databases, and SQL queries (Advantage)

We offer

Hybrid work model