Test Automation Lead

12 hours ago

Noida Uttar Pradesh, India Dailoqa Full time

Role Overview As a Test Automation Lead at Dailoqa you ll architect and implement robust testing frameworks for both software and AI ML systems You ll bridge the gap between traditional QA and AI-specific validation ensuring seamless integration of automated testing into CI CD pipelines while addressing unique challenges like model accuracy GenAI output validation and ethical AI compliance Key Responsibilities Test Automation Strategy Framework Design Design and implement scalable test automation frameworks for frontend UI UX backend APIs and AI ML model-serving endpoints using tools like Selenium Playwright Postman or custom Python Java solutions Build GenAI-specific test suites for validating prompt outputs LLM-based chat interfaces RAG systems and vector search accuracy Develop performance testing strategies for AI pipelines e g model inference latency resource utilization Continuous Testing CI CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions Jenkins or GitLab CI CD Implement shift-left testing by embedding automated checks into development workflows e g unit tests contract testing AI ML Model Validation Collaborate with data scientists to test AI ML models for accuracy fairness stability and bias mitigation using tools like TensorFlow Model Analysis or MLflow Validate model drift and retraining pipelines to ensure consistent performance in production Quality Metrics Reporting Define and track KPIs Test coverage code data scenarios Defect leakage rate Automation ROI time saved vs maintenance effort Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews Drive adoption of AI-specific testing tools e g LangChain for LLM testing Great Expectations for data validation Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development Ability to communicate technical risks to non-technical stakeholders Collaborative mindset to work with cross-functional teams data scientists ML engineers DevOps Requirements Technical Requirements Must-Have 8-10 years in test automation with 2 years validating AI ML systems Expertise in Automation tools Selenium Playwright Cypress REST Assured Locust JMeter CI CD Jenkins GitHub Actions GitLab AI ML testing Model validation drift detection GenAI output evaluation Languages Python Java or JavaScript Certifications ISTQB Advanced CAST or equivalent Experience with MLOps tools MLflow Kubeflow TFX Familiarity with vector databases Pinecone Milvus and RAG workflows Strong programming scripting experience in JavaScript Python Java or similar Experience with API testing UI testing and automated pipelines Understanding of AI ML model testing output evaluation and non-deterministic behavior validation Experience with testing AI chatbots LLM responses prompt engineering outcomes or AI fairness bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile Scrum methodology and tools like Azure Boards

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