Senior Engineering Manager I - Quality Engineering

Key Responsibilities

• Architect and implement scalable Test Engineering Platforms leveraging GenAI for cloud-native and microservices applications.
• Define test automation strategies, integrating with Agile, DevOps, and CI/CD ecosystems using TDD, BDD, and DDD principles.
• Analyze and enhance existing test automation frameworks, QE processes, governance models, and database schemas.
• Optimize branching strategies, release cycles, and DevOps toolchain integration for CI/CD enablement.
• Develop Quality Engineering transformation roadmaps, aligning with business and technology goals.
• Introduce AI-driven automation, self-healing test frameworks, and predictive analytics to elevate QE maturity.
• Conduct maturity assessments, identifying gaps and implementing direct, hands-on solutions.
• Establish AI-powered QE frameworks, leveraging predictive analytics and ML-driven defect prevention.
• Oversee performance engineering and reliability testing, ensuring optimal application performance under varying conditions.
• Implement risk-based testing models, integrating security, accessibility, and compliance testing into SDLC.
• Drive observability and monitoring adoption, leveraging test analytics for real-time quality insights.
• Establish shift-left testing strategies for early defect detection within development workflows.
• Define cloud-native testing strategies for AWS, Azure, and GCP workloads.
• Develop quality metrics frameworks, tracking test effectiveness, automation ROI, and defect leakage.
• Lead Test Automation Centers of Excellence (CoE), driving innovation in QE methodologies and tools.
• Conduct technical workshops, assessments, and capability-building sessions to uplift QE maturity.
• Optimize toolchain selection, test data management, and environment provisioning for enhanced efficiency.
• Implement testing strategies for microservices, APIs, containers, and serverless architecture

Key Responsibilities

• Architect and implement scalable Test Engineering Platforms leveraging GenAI for cloud-native and microservices applications.
• Define test automation strategies, integrating with Agile, DevOps, and CI/CD ecosystems using TDD, BDD, and DDD principles.
• Analyze and enhance existing test automation frameworks, QE processes, governance models, and database schemas.
• Optimize branching strategies, release cycles, and DevOps toolchain integration for CI/CD enablement.
• Develop Quality Engineering transformation roadmaps, aligning with business and technology goals.
• Introduce AI-driven automation, self-healing test frameworks, and predictive analytics to elevate QE maturity.
• Conduct maturity assessments, identifying gaps and implementing direct, hands-on solutions.
• Establish AI-powered QE frameworks, leveraging predictive analytics and ML-driven defect prevention.
• Oversee performance engineering and reliability testing, ensuring optimal application performance under varying conditions.
• Implement risk-based testing models, integrating security, accessibility, and compliance testing into SDLC.
• Drive observability and monitoring adoption, leveraging test analytics for real-time quality insights.
• Establish shift-left testing strategies for early defect detection within development workflows.
• Define cloud-native testing strategies for AWS, Azure, and GCP workloads.
• Develop quality metrics frameworks, tracking test effectiveness, automation ROI, and defect leakage.
• Lead Test Automation Centers of Excellence (CoE), driving innovation in QE methodologies and tools.
• Conduct technical workshops, assessments, and capability-building sessions to uplift QE maturity.
• Optimize toolchain selection, test data management, and environment provisioning for enhanced efficiency.
• Implement testing strategies for microservices, APIs, containers, and serverless architecture