Lviv, Ivano-Frankivsk, Remote
We’re seeking an intermediate-level QA Engineer who thrives on untangling complex, data-rich systems and is eager to test conversational AI products. You’ll design and execute thorough manual tests for intricate web, API, and database flows, validate data with SQL, and log defects that drive real fixes. While our current focus is manual testing, you’ll help lay the groundwork for future automation, bringing an analytical mindset and clear, B2+ English communication to cross-functional teamwork. Experience—or strong interest—in testing AI chatbots/NLP solutions is highly valued, and you’ll have room to grow into automation and cloud-based testing as the product evolves.
As a QA Engineer on the Conversational Analytics AI project, you will be responsible for ensuring the accuracy, reliability, and usability of a product designed to transform how users interact with data through natural language. This role is critical in validating that the AI provides correct, timely, and actionable insights - especially as it replaces manual data queries and supports both technical and non-technical users. You will work cross-functionally to test complex data workflows, integrations with the data lake, and conversational logic. Your work will directly impact team productivity, onboarding speed, and customer satisfaction by ensuring a smooth, high-quality user experience from day one.
The Conversational AI project aims to enhance how teams access and interact with data by enabling natural language queries. It reduces the workload on data analysts by handling routine and moderately complex questions, allowing analysts to focus on strategic tasks. Non-technical users gain instant access to insights without needing technical tools or support. This improves onboarding speed, team productivity, and decision-making efficiency. The project is expected to drive measurable improvements in task completion rates, query response time, analyst efficiency, and overall user satisfaction. It’s built with a customer-first mindset, using future customer quotes to validate its value before development begins.
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