Role: QA Lead
Experience: 8-12 Years
Location: Whitefield, Bangalore
Job Summary:
We are seeking a highly experienced Senior QA Engineer with 812 years of expertise in architecting and executing comprehensive quality assurance strategies for complex cloud-native, data-driven, and AI-powered applications. The candidate will be responsible for ensuring the reliability, accuracy, and performance of large-scale systems that integrate real-time data processing and intelligent model insights.
The ideal candidate must possess an understanding of cloud infrastructure, data integrity validation, and also the challenges of testing AI/ML models. Should be an expert in designing automated frameworks using modern tools like Playwright or Cypress to validate high-bandwidth data flows and complex web/mobile interfaces.
Key Responsibilities:
- Design and lead a comprehensive QA roadmap that covers data pipelines, AI model integration, and cloud-native backend services.
- AI & Model Validation: Establish testing protocols to validate AI/ML model outputs, focusing on accuracy, performance benchmarking, and bias detection.
- Build and maintain scalable, Shift-Left automation frameworks using Playwright or Cypress to accelerate the CI/CD pipeline and ensure UI/UX consistency across platforms.
- Ensure the reliability of high-volume data flows by validating ingestion, processing, and storage across cloud-based data warehouses and real-time streams.
- Architect and execute load and stress testing to ensure the platform handles high concurrency and data-intensive workloads without degradation.
- Implement security testing standards to protect sensitive data and ensure all cloud communications meet industry encryption and authorization protocols.
- Root Cause Analysis: Utilize cloud monitoring and logging tools (such as Azure Monitor or Log Analytics) to identify and resolve complex system bottlenecks.
- Cross-Functional Collaboration: Partner with Data Scientists, Developers, and Product teams to define quality gates and ensure features are built for maximum testability.
- Define best practices for testing methodologies and mentor junior QA engineers in modern automation and data testing patterns.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 812 years of professional experience in software quality assurance, focusing on cloud and data-driven systems.
- Drive the technical roadmap for quality by implementing testing layers (Unit, Integration, and System) that ensure the entire ecosystem remains modular and scalable
- Strong hands-on experience with modern E2E testing frameworks such as Playwright or Cypress, and the ability to integrate them into automated CI/CD workflows.
- Understanding of testing AI-powered systems, including knowledge of model drift, evaluation metrics (precision/recall), and non-deterministic testing.
- Hands-on experience with Microsoft Azure services to begin with and knowledge of other cloud providers (AWS/GCP) is a significant plus.
- Strong proficiency in JavaScript/TypeScript (essential for Playwright/Cypress), Python, or Java for developing custom automation tools.
- Expert knowledge of SQL and NoSQL databases, with the ability to write complex queries to validate data integrity across distributed systems.
- Proven ability to oversee the full Software Development Lifecycle, from initial requirement analysis to production release and post-launch monitoring.
Good To Have:
- Familiarity with Generative AI (GenAI) testing and LLM evaluation techniques.
- Microsoft Certified: Azure AI Engineer Associate or Azure Data Engineer Associate.
- Experience with performance testing tools like JMeter, Gatling, or Locust.
