ai is a fast-growing vertical SaaS start-up, funded by Insight Partners, Peak XV (Surge), InfoEdge, Vertex Ventures, and Tenacity Ventures that provides innovative software solutions for the landscape, paving & construction industries in the United States. Our mission is to help businesses in this space improve their operations and grow their revenue through our simple & easy-to-use software platforms.
As a QA Engineer, you will be responsible for providing testing support to our SDLC lifecycle to improve the quality of our products. Review tests around critical flows and automate them to continuously improve the quality of our software products.
This position is critical for us and we seek an experienced QA engineer who can work as a team player and participate in all SCRUM related activities, and deliver high quality work within defined timelines.
Develop test cases for upcoming features across unit, integration, and acceptance layers
Initiating manual execution of test cases and collaborate with Product & Dev teams for preparation of UAT sheets
Writing and maintaining functional automation scripts
Learn and implement new tools and technologies whenever required for improving the quality
Contribute to the shift-left testing approach, ensuring early detection and resolution of issues
Provide timely support for production issues by analyzing application behaviour, APIs, logs, data, and configurations
Solid testing fundamentals with 2-5 years of work experience in all phases of STLC
Experience in Web testing, Mobile Apps testing (Android and iOS), & API testing
Experience in design and creation of Test Cases based on Requirements document.
Experience in automation testing using any tools such as Appium, Selenium, RestAssured, Playwright, etc.
Working knowledge of web services, databases, and web technologies
Analytical & flexible in working style and mindset
Basic knowledge about SQL
Experience working with JIRA
Familiarity with AI-assisted QA tools and techniques for test case generation, test data generation, test automation, exploratory testing, and defect investigation.
Experience using AI tools such as ChatGPT, Claude, Cursor, GitHub Copilot, or similar tools to improve QA productivity.
Ability to use AI for test failure analysis, root cause analysis, regression optimization, and test coverage improvement.
Basic understanding of testing AI-powered features, including concepts such as hallucination, accuracy, relevance, robustness, and prompt-related risks.
📌 QA Engineer (Agile) (Noida)
🏢 Beam AI
📍 Noida