QA Lead — AI Learning Platform (Remote, Release Authority)

CGS Nexus; United States; Remoto; USD 50.000 - 72.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

Dental insurance

Life insurance

RRSP

Remote work from home

Career growth opportunities

Collaborative environment

Descrizione del lavoro

CGS Immersive is seeking a hands-on Quality Assurance Lead to own the QA process and ensure release confidence for an AI learning platform. The role grants authority to pause production if quality criteria are not met and requires building a comprehensive testing strategy that protects learner outcomes.

You will combine AI-assisted testing with traditional QA, maintaining thorough coverage and collaborating with Product and Engineering to resolve issues before clearance.

Competenze

• Proven experience establishing and owning a QA process for a software product.
• Hands-on manual testing with clear, comprehensive test scenarios.
• Practical knowledge of test planning, regression testing, exploratory testing, change‑impact analysis, defect management and release readiness assessment.
• Working proficiency in Jira, including interpreting epics, stories, acceptance criteria and release information.

Mansioni

• Establish and own the QA strategy, testing standards, reusable test library and release criteria. Make testing a consistent part of planning and delivery.
• Create and maintain a functional map of the application, covering user roles, journeys, features and dependencies. Document expected behaviour and learning outcomes so the team has a clear, agreed definition of what good looks like.
• Review Jira epics, user stories, acceptance criteria and release updates to understand the purpose of each change. Clarify gaps with Product and link requirements to test cases, results and defects.
• Design and execute comprehensive functional, integration, exploratory and regression tests. Cover complete user journeys, negative scenarios, boundary conditions, permissions, interrupted sessions and recovery paths.
• Analyse each release for its impact on existing functionality and dependencies. Prioritise testing by user impact and risk, and verify that fixes resolve the issue without breaking other areas.
• Evaluate simulation behaviour, AI coaching, scoring and critique against learning objectives and rubrics agreed with subject matter experts. Check that feedback reflects the learner’s actual performance and provides useful guidance.
• Maintain representative AI test scenarios and approved reference examples. Repeat evaluations to detect unacceptable variation, lost conversational context, unsupported claims, biased or inappropriate feedback, and attempts to bypass instructions.
• Document findings in Jira with reproducible steps, environment and version details, expected and actual results, evidence, severity and user impact. Capture prompts and conversation context for AI issues, and track defects through retesting and closure.
• Provide a documented QA release assessment covering tests completed, coverage gaps, unresolved defects and remaining risks. Exercise release‑blocking authority when evidence does not support confidence.
• Investigate production issues with Engineering, identify why regressions escaped detection and add tests that prevent recurrence. Track production defect severity, repeat regressions and coverage of critical journeys to demonstrate improvement.
• Identify repetitive tests suited to automation and work with Engineering to implement them, while maintaining strong manual and exploratory coverage.

Conoscenze

QA process ownership

Manual testing

Test planning

Jira proficiency

Attention to detail

Communication

Release readiness

Formazione

ISTQB certification or equivalent

Strumenti

Jira

Xray

Zephyr

TestRail

Descrizione del lavoro

CGS Immersive is seeking a hands-on Quality Assurance Lead to own the QA process and ensure release confidence for an AI learning platform. The role grants authority to pause production if quality criteria are not met and requires building a comprehensive testing strategy that protects learner outcomes.

You will combine AI-assisted testing with traditional QA, maintaining thorough coverage and collaborating with Product and Engineering to resolve issues before clearance.