QA Lead

Senior QA Lead

We are looking for a Senior QA Lead to define, lead, and execute comprehensive end-to-end (E2E) testing strategies across complex, integrated platforms. The ideal candidate will have strong experience in E2E validation across Web, Mobile, and API layers, with a focus on automation, AI-driven quality practices, and enterprise-scale quality governance.

Key Responsibilities

• Strategy & Oversight: Define and drive the comprehensive E2E QA strategy and quality standards for all integrated cross-platform applications and services.
• Lead Complex E2E Testing: Design, coordinate, and lead complex end-to-end testing efforts, serving as the subject matter expert for integrated systems.
• Cross-Platform Coordination: Lead the design and execution of integrated testing processes that validate user workflows across multiple systems.
• Exploratory & Usability Testing: Conduct targeted exploratory and usability testing sessions on high-risk features and major releases to uncover experience gaps.
• Release Certification: Serve as the final quality gatekeeper, certifying major releases and high-risk features based on E2E test outcomes and quality metrics.
• Production Monitoring: Establish processes to monitor production quality signals (e.g., bug reports, crash analytics, user feedback) and feed insights into continuous improvement cycles.
• Defect Management: Oversee the defect life cycle, ensuring efficient reporting, RCA, and resolution for complex, multi-system failures.
• AI Integration: Evaluate, pilot, and integrate AI/ML-driven testing tools for visual regression, self-healing tests, intelligent data generation, and predictive defect management.
• Leadership & Mentorship: Guide engineering teams on advanced E2E testing methodologies, test design, and execution best practices.

Requirements Qualifications

• Experience: 10+ years in Quality Engineering, including 3+ years in a senior or lead role with an emphasis on E2E or system-level testing.
• Cross-Platform Expertise: Proven experience in testing integrated, cross-platform systems (Web, Mobile, APIs).
• AI/ML Testing Exposure: Familiarity with AI-enabled testing tools or predictive quality methodologies.
• Methodology: Strong understanding of Agile, SDLC, and STLC processes.

Technical Proficiency

• API testing tools: Postman, SoapUI (or equivalent)
• Bug tracking: Jira, Azure DevOps
• Version control: Git
• Communication: Strong analytical, organizational, and communication skills; ability to convey complex risks to technical and business stakeholders.

Desirable Skills (Preferred)

• Automation Strategy: Knowledge of AI-based test automation frameworks and CI/CD integration strategies.
• Performance Testing: Familiarity with load/performance testing tools (JMeter, LoadRunner, Gatling, etc.).
• Cloud/Containerization: Understanding of AWS and containerization (Docker, Kubernetes) for test environment management.