QA Engineer (Conversational AI)
About the role
Home NU0063 QA Engineer (Conversational AI) 3-5 Full-Time
About Us Nurix.ai is at the forefront of AI innovation, developing cutting-edge AI and LLM solutions to enhance productivity and automation. B We envision a world powered by super-intelligent AI agents that transform how businesses engage with customers. Our cutting-edge AI agents do more than just solve problems, they create opportunities.
About
the Role We 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, India Key
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).