QA Lead - Adobe Experience Manager (AEM)

BS Resourcing · India

We are seeking an experienced Quality Assurance Manager with 15+ years of experience in Quality Engineering, Test Management, Test Automation, and Quality Transformation.

The ideal candidate will play a key role in strengthening and evolving the organization's Quality Assurance Center of Excellence (QA COE) by enhancing governance frameworks, quality processes, standards, metrics, tooling strategies, and delivery excellence practices.

This role requires extensive experience across Adobe Experience Manager (AEM), Digital Experience Platforms, Enterprise Web Applications, AI-enabled solutions, and Customer Experience platforms.

Salesforce Marketing Cloud (SFMC) is a nice to have.

The candidate should demonstrate strong leadership capabilities combined with expertise in automation frameworks such as Playwright and Robot Framework, API testing, enterprise quality engineering, and modern Agile delivery practices, enabling the organization to accelerate automation adoption, improve quality visibility, and drive continuous improvement across delivery teams.

Role Objective

Lead the evolution of Quality Engineering by enhancing QA COE capabilities, strengthening stakeholder engagement, improving testing maturity, driving automation adoption, and ensuring quality excellence across Adobe Experience Manager (AEM), Salesforce Marketing Cloud (SFMC), Customer Experience Platforms, Enterprise Digital Solutions, AI-enabled applications, and enterprise quality tooling ecosystems.

KEY RESPONSIBILITIES

QA Strategy, Governance & Continuous Improvement

• Enhance and continuously improve QA governance, standards, processes, metrics, and best practices within the QA COE. • Drive quality engineering maturity across delivery teams through standardization, automation, and continuous improvement initiatives. • Define and monitor quality KPIs, test effectiveness metrics, defect leakage trends, and release readiness indicators. • Promote Shift-Left testing practices and quality ownership across delivery teams. • Identify opportunities to improve testing efficiency, quality outcomes, and predictability delivery through automation, process, and AI optimization. • Establish enterprise-wide quality engineering standards and governance frameworks.

AI Adoption & Productivity Enablement

• Promote the effective use of AI technologies to improve Quality Engineering productivity and delivery efficiency. • Identify opportunities to leverage Generative AI and AI-enabled solutions for:

• Test design acceleration

• Test optimization

• Defect analysis

• Documentation generation

• Knowledge management

• Quality reporting

• Team productivity

• Evaluate emerging AI solutions capable of accelerating delivery while maintaining governance and compliance standards.

• Drive adoption of AI-enabled practices across Quality Engineering teams. • Contribute to organizational innovation initiatives and continuous improvement programs. • Ensure responsible, secure, and business-aligned use of AI technologies.