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7 days ago
About the RoleWe are seeking a highly motivated and detail-oriented Quality Assurance (QA) Engineer to join our team. You will play a key role in ensuring the reliability, accuracy, and user experience of our Conversational AI systems. This role involves testing dialogue models, integrations with NLP/LLM-based backends, and end-to-end conversational workflows across multiple platforms (chat,voice, and integrations with enterprise systems).Location: Bengaluru, IndiaKey Responsibilities● Test Planning & Strategy○ Develop and execute comprehensive test plans for conversational AI features, including NLP pipelines, dialogue flows, integrations, and APIs.○ Design functional, regression, performance, and exploratory test cases specific to conversational interfaces.● Conversational Testing○ Validate intent recognition, entity extraction, context handling, and multi-turn dialogue management.○ Test conversational flows for accuracy, completeness, and user experience. Perform scenario-based and edge-case testing to capture unexpected user inputs.● Automation & Tooling○ Build automated test scripts for API endpoints, dialogue flows, and ML model outputs.○ Work with frameworks like Postman, Cypress, PyTest, or custom NLP testing tools.○ Contribute to CI/CD pipelines with automated regression tests.● Collaboration○ Partner with Data Scientists, ML Engineers, and Product Managers to define acceptance criteria for AI-driven features.○ Provide feedback on conversational design and model performance.○ Collaborate with DevOps on load testing and monitoring production systems.● Quality Advocacy○ Ensure conversational AI products meet high standards for accuracy, robustness, fairness, and usability.○ Help define and track KPIs (e.g., intent accuracy, response latency, conversation success rate).Qualifications● 3+ years of QA/testing experience, preferably with AI, ML, or NLP products.● Strong understanding of API testing, automated frameworks, and scripting languages (Python, JavaScript, or similar).● Experience testing chat agents, voice agents, or conversational interfaces is a plus.● Familiarity with NLP concepts: intents, entities, context, LLMs, and dialogue managementframeworks (e.g., Rasa, Dialogflow, LLM APIs).● Experience with CI/CD pipelines and version control (Git).● Excellent problem-solving, analytical, and communication skills.Nice-to-Haves● Exposure to A/B testing and model evaluation.● Experience with cloud platforms (AWS, GCP, Azure).● Familiarity with accessibility and localization testing for multilingual agents..● Interest in AI ethics, fairness, and bias testing.
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