Location : Berlin HQ or Remote in Europe Department : Product & Engineering About Synthflow At Synthflow, we are redefining how businesses interact with customers by deploying cutting-edge Voice AI solutions across telephony and SIP systems. Our products empower enterprises to deliver intelligent, seamless, and scalable voice interactions. Join us to shape the future of conversational AI. Role Overview We are looking for a meticulous and driven Manual QA Engineer to ensure the quality and reliability of our Voice AI products. You will play a key role in shaping the customer experience by developing and executing manual test strategies, collaborating closely with product managers and developers, and continuously improving our QA practices in a fast-paced, agile environment. Responsibilities • Develop, maintain, and execute comprehensive manual test plans and detailed test cases for Synthflow’s Voice AI products. • Perform exploratory, functional, and regression testing to uncover issues early and ensure product stability before release. • Collaborate with developers and product managers to deeply understand requirements and ensure thorough test coverage for all features and enhancements. • Identify, document, and manage defects using test management tools, ensuring clear, actionable reporting and tracking to resolution. • Provide actionable feedback to improve product quality, usability, and overall user experience. • Refine and enhance QA processes to align with agile development workflows, ensuring efficient and effective test cycles. Qualifications • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. • 5 years of experience in software quality assurance, with a strong emphasis on manual testing. • Hands-on experience with test management tools such as Qase, Jira, Linear, TestRail, or similar platforms. • Basic working knowledge of databases (RDBMS or NoSQL) for data validation and integrity checks. • Familiarity with CI/CD pipelines and agile methodologies is advantageous. • Exposure to AI concepts, particularly prompting and conversational AI models, is a plus.