Test Delivery & Quality Assurance
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Perform end-to-end manual and automated testing across Online Tools
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Execute testing across functionality, performance, reliability, stability, compatibility, and integrations.
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Conduct gap analysis between requirements and existing solutions.
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Ensure user stories are testable, with clear acceptance criteria
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Define and enforce quality standards in PI planning and sprint cycles.
Develop and maintain:
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Test plans
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Test scenarios
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Test cases
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Execution results and traceability
Automation & Engineering
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Build and maintain automation frameworks and reusable test assets.
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Execute and maintain automated regression suites
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Implement API and UI automation testing aligned to engineering standards.
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Validate integration points across legacy and external systems.
Data & Calculation Validation
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Validate financial calculations in quote tools and calculators
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Perform data integrity and reconciliation testing (incl. big data outputs)
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Use SQL and database tools to validate backend data accuracy
Agile & Delivery Contribution
Actively participate in:
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Backlog refinement
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Sprint planning
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PI planning
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Contribute to team predictability through test coverage insights
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Drive early defect detection and prevention practices
Stakeholder & Team Collaboration
Collaborate with:
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Developers
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Product Owners
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Business Analysts
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Demonstrate test outcomes and solution quality to stakeholders
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Promote collective ownership of quality within the squad
Continuous Improvement & Leadership
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Report on QA trends and continuously improve testing practices
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Mentor junior testers and provide technical guidance
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Support automation strategy and QA CoP initiatives
AI-Enabled QA Responsibilities
AI-Driven Testing
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Apply AI tools for:
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Test case generation
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Test data creation
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Defect prediction and risk-based testing
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Use AI to improve test coverage, speed, and accuracy
Intelligent Test Automation
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Leverage AI-assisted automation for:
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Self-healing test scripts
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Smart element identification
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Maintenance reduction
Quality Insights & Analytics
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Use AI and analytics to:
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Identify defect patterns
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Predict high-risk areas
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Improve release confidence
AI Governance & Responsible QA
Ensure:
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AI outputs are validated and explainable
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Bias and incorrect predictions are mitigated
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AI-generated tests meet quality standards
Productivity & Time-to-Value
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Use AI-assisted development and testing tools to reduce cycle time and improve efficiency
