Automation Tester

About Agilysys

Agilysys has been a leader in hospitality software for over 40 years, providing innovative cloud-native SaaS and on-premises guest-centric technology solutions for various sectors including gaming, hotels, resorts, cruises, corporate foodservice, restaurants, universities, healthcare, and sports and entertainment. We offer a comprehensive suite of software solutions covering point-of-sale (POS), property management (PMS), inventory and procurement, payments, and other applications designed to manage the entire guest experience. Our dedication to hospitality excellence, extensive product range, and customer-focused service have established us as a reliable partner for major global hospitality organizations. Significant recent investments in research and development have led to the modernization of nearly all our established software solutions, aimed at helping clients enhance guest loyalty, boost revenue, and improve operational efficiency. Agilysys operates across the Americas, Europe, the Middle East, Africa, and Asia-Pacific.

Required Skills & Experience

• Proficiency in fundamental testing principles, including requirements analysis, test design, risk-based testing, and defect analysis.
• Demonstrated experience in test automation, with a preference for Playwright, or alternatively Selenium/Cypress.
• Solid coding abilities in JavaScript, TypeScript, Java, or Python.
• Experience with API and integration testing.
• Familiarity with Continuous Integration and Continuous Deployment (CI/CD) pipelines.
• Capability to review, refine, and validate AI-generated test cases and automation scripts.
• Practical skills in prompt engineering for test generation, identifying edge cases, and assessing regression impact.
• A strong sense of ownership and the ability to apply human judgment in the loop.

Good to Have

• Experience in log and data analysis.
• Proficiency in using AI tools to analyze test failures and summarize extensive output data.

Not Required

• Experience in building Large Language Models (LLMs) or AI models.
• Implementation of Retrieval-Augmented Generation (RAG) or vector databases.
• Development of autonomous AI agents.