QA (Product)

Product

Remote

2 \- 5 years experience

###### **Responsibilities**

We are looking for a detail\-oriented QA Engineer with at least 3 years of hands\-on experience in manual and automation testing. You will play a critical role in ensuring product quality for our web, mobile, and API platforms. This role is ideal for someone who is strong in manual testing and is comfortable contributing to automation.

• *Key Responsibilities**

• Collaborate with product managers, AI engineers, and developers to define QA strategies for LLM and voice\-based features.
• Design and execute test cases for functional, regression, integration, and performance testing.
• Test conversational AI/LLM features for accuracy, response relevance, context retention, hallucination detection, and prompt robustness.
• Conduct voice testing across multiple platforms, focusing on speech recognition, TTS, latency, and conversational flow validation.
• Build and maintain automated regression test suites (preferred stack: Selenium \+ Java/TestNG, with exposure to Cypress/Playwright).
• Perform API testing using Postman/RestAssured, including validation of AI/voice APIs.
• Define and track QA metrics such as response accuracy, latency benchmarks, and defect leakage.
• Collaborate with cross\-functional teams to continuously improve test coverage and product reliability.

• *Required Skills \& Qualifications**

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 3–5 years of proven QA experience (manual \+ automation).
• Strong knowledge of QA methodologies, SDLC, STLC, and Agile/Scrum practices.
• Hands\-on experience with automation frameworks (Selenium, Cypress, or Playwright).
• Experience testing LLM\-based features (OpenAI, Anthropic, or similar APIs).
• Practical knowledge of voice testing, including ASR (Automatic Speech Recognition), NLP pipelines, and TTS validation.
• Strong analytical and communication skills with the ability to think from the end\-user perspective.

• *Good to Have**

• Experience with performance testing (JMeter, Locust) for LLM and voice workloads.
• Familiarity with evaluation metrics for AI systems (e.g., BLEU, ROUGE, WER for speech).
• Hands\-on with cloud\-based AI testing tools and platforms (BrowserStack, Sauce Labs, or Speech\-to\-Text benchmarks).
• ISTQB or other QA certifications.

###### **Skills Required**

Primary Skills

QA