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
