About the client -
We are a world-changing team of AI researchers and engineers working on the cutting edge of generative AI. We are building systems that work across telephony, chat, video, email & text to assist & accelerate the human workforce with artificial agents.
Our focus is on helping customers improve their outcomes in the areas of Business Process (Customer service, IT support, Accounting, Human resources, Legal services, Marketing, IP Legal, etc.
5 days working - Hyderabad
Rounds: 1 Virtual, 1 Physical
Location: Hitech City, Hyderabad
Role Overview
We are looking for a QA Engineer who is passionate about ensuring quality in AI-driven voice assistant products. This role involves a mix of deep manual testing, API validation, and basic automation work using Python.
Key Responsibilities
Perform extensive manual testing of conversational AI assistants -- reviewing call recordings, chat transcripts, and verifying assistant responses.
Validate call flow quality, identify interruptions, speech recognition errors, and prompt misbehaviors.
Test and verify new product features, enhancements, and bug fixes.
Write detailed, scenario-based test cases for voice and text interactions.
Perform API testing (manual or using tools like Postman) and validate integration between backend services.
Execute basic automation scripts in Python for repetitive API or functional tests.
Collaborate with developers and product teams to understand requirements and identify test coverage.
Contribute to prompt testing, counter-prompt validation, and comparison testing against competitor products.
Support release validation for multiple client-specific AI assistants.
Qualifications
3+ years of QA experience in a product or SaaS environment.
Strong interest and proven ability in manual testing -- especially testing user experience, voice/call flows, and real interactions.
Hands-on experience with API testing using tools like Postman, Insomnia, or similar.
Basic Python scripting knowledge (able to read, run, or slightly modify automation scripts).
Clear understanding of QA concepts -- test planning, test case design, regression, defect tracking, etc.
Good communication skills -- able to clearly articulate issues, document observations, and collaborate with cross-functional teams.
Curiosity to understand how AI assistants think, speak, and behave -- and eagerness to find where they fail.
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