Lead Quality Engineer - Salesforce

Summary:

We are seeking an experienced Manual QA Lead with an AI mindset to drive quality excellence across complex enterprise and eCommerce applications. This role requires a strong foundation in manual testing, leadership capabilities, and the ability to leverage AI/GenAI tools to enhance testing efficiency, coverage, and insights.
The ideal candidate will lead QA initiatives, mentor teams, and champion intelligent, data-driven quality practices that integrate traditional QA with AI-enabled approaches.

Responsibilities:

• Lead end-to-end test strategy, planning, and execution for releases (break-fix, monthly, and large-scale deployments)
• Manage and mentor a team of QA engineers, ensuring clear ownership and accountability
• Drive risk-based testing approaches and proactively identify quality risks
• Collaborate with cross-functional teams (Dev, Product, DevOps, Business)
• Define and execute functional, regression, integration, and UAT testing
• Ensure high-quality test case design, traceability, and coverage
• Validate complex workflows across integrated systems (e.g., Salesforce, SAP, APIs, middleware)
• Drive defect lifecycle management and root cause analysis
• Leverage AI tools (e.g., Copilot, GenAI, ML models) for:
• Test case generation and optimization
•   Defect prediction and intelligent triaging
•   Test data generation
•   Risk identification and anomaly detection
• Identify opportunities to reduce manual effort using AI-assisted testing approaches
• Partner with engineering to introduce AI in test automation acceleration strategy
• Align QA activities with release management, CAB/eCAB processes, and code freeze policies
• Ensure test readiness across environments (QA, staging, production validation)
• Support production deployments, smoke testing, and hypercare validation
• Define and publish quality dashboards and KPIs:
•        Defect leakage
•        Test coverage
•        Release quality index
•        Cycle time reduction
• Provide leadership-ready insights and risk-based reporting
• Drive retrospectives and implement lessons learned
• Introduce process improvements using AI insights and analytics
• Promote a culture of ownership, accountability, and innovation

Qualification:

• Bachelor’s degree in Computer Science, Engineering, or equivalent
• 8+ years of QA experience, with 2–4 years in leadership role
• Strong expertise in manual testing for enterprise applications
• Experience in eCommerce domain or large-scale integrated systems
• Strong stakeholder communication (business + leadership)
• Proven ability to drive ownership and accountability in teams
• Excellent risk identification and escalation mindset
• Coaching and mentoring QA engineers and leads
• Ability to operate in high-pressure release environments
• Hands-on experience with:
•         Test management tools (Azure DevOps, Jira, etc.)
•         API testing (Postman/REST tools)
•        SQL/database validation
• Nice to have:
• Exposure to AI/ML concepts in QA or software engineering
• Experience using tools like GitHub Copilot / ChatGPT / AI-based QA tools
• Ability to translate business problems into AI-driven QA solutions