QA Engineer

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.