Quality Assurance Automation Lead

Experience - 5-6 yearsLocation - Bengaluru/Hyderabad/MangaloreAI/ML Product Testing | Automation | Test Strategy | Quality LeadershipAbout the RoleWe are looking for a QA Lead with 5–6 years of experience in leading QA activities, designing test strategies, and ensuring the delivery of high-quality software. The ideal candidate has solid experience testing AI/ML-driven products, including LLM applications, ML pipelines, data-processing systems, and intelligent automation platforms. This role requires strong analytical thinking, hands-on testing capability, leadership skills, and a deep understanding of quality processes for AI-based systems.You will work closely with product, data science, engineering, and DevOps teams to define and implement robust testing frameworks tailored for traditional systems as well as AI-based features.Key Responsibilities1. QA Strategy & PlanningLead QA efforts across the full SDLC for AI/ML and software products.Design test strategies for:AI/ML models and inference APIsLLM-driven features (chatbots, RAG pipelines, automation workflows)Microservices and backend APIsWeb/mobile applicationsDefine test plans, scope, timelines, and acceptance criteria.2. AI/ML Product TestingDesign and execute test scenarios for:Model accuracy, drift, bias, hallucination testingPrompt/response validation for LLM featuresModel versioning and regression testingRAG pipeline validation (embedding accuracy, retrieval quality)AI-driven UX workflowsWork closely with ML engineers to understand model behaviour, datasets, and performance metrics.3. Automation TestingBuild or oversee automation frameworks for UI, API, and data validation.Tools commonly used:Selenium / Playwright / CypressPostman / NewmanPyTest / Robot FrameworkJMeter / Locust for performanceDevelop automated test suites for continuous integration pipelines.4. Functional & Non-functional TestingLead end-to-end functional testing across web/mobile platforms.Handle performance, load, scalability, and security testing.Ensure data validation, API correctness, and integration quality.5. Leadership & CollaborationLead and mentor a team of QA engineers (2–5 members).Conduct test reviews, defect reviews, root cause analysis, and quality audits.Work with cross-functional teams including PMs, DevOps, and ML engineers.Contribute to sprint planning, story estimation, and release readiness.6. Process & Quality ImprovementsEstablish QA best practices, guidelines, and templates.Drive continuous improvement of processes across automation, manual QA, and AI testing.Set up dashboards and metrics for test coverage, defect trends, and release quality.Required Skills & ExperienceCore QA Skills5–6 years of hands-on QA experience including test planning, test case design, defect management.Strong experience in manual & automation testing.Experience validating REST APIs, backend services, and data pipelines.AI/ML QA ExpertiseUnderstanding of ML model lifecycle—training, testing, deployment.Experience testing:LLM-based features (Generative AI, chatbots, AI copilots)Recommendation systems, predictive analytics systemsRAG or vector-search-based applicationsAbility to define metrics for accuracy, bias, drift, hallucinations, and quality.Automation ToolsHands-on with automation frameworks:Selenium, Playwright, Cypress, PyTest, Robot , etc.API automation experience (Postman/Newman, REST Assured).Exposure to CI/CD and automated pipeline integration.Technical KnowledgeUnderstanding of microservices, cloud environments, and distributed systems.Basics of Python or Java for writing automation scripts.Familiarity with tools like Jira, TestRail, Git, Jenkins, Docker.Soft SkillsExcellent analytical and problem-solving skills.Strong communication, documentation, and stakeholder management.Ability to lead testing efforts and coordinate across teams.Nice-to-HaveExperience with MLOps workflows and model monitoring.Knowledge of cloud platforms (AWS/GCP/Azure).Understanding of data quality validation techniques.Exposure to security testing and compliance.