QA AI API Function Tester

"Quality Assurance (QA) – Client Engagement Console (CEC)

Role Overview

The QA Engineer ensures the CEC platform delivers reliable, accurate, and audit-ready outcomes, especially for AI-driven recommendations such as “next best actions.” This role is critical in validating data integrity, AI outputs, system performance, and regulatory compliance, while enabling a high-quality, scalable MVP across Wealth, Health, and Career.

Key Responsibilities

• Test Strategy & Planning
  
  

Define and implement a comprehensive QA strategy covering functional, data, AI/ML, and non-functional testing

Develop test plans, test cases, and automation strategies aligned with MVP and Wave-based delivery

Ensure coverage across end-to-end workflows of the CEC platform

• Functional & Integration Testing
  
  

Validate Core Features Such As

Client 360 views

Signal ingestion and prioritization

“Next Best Actions” recommendations

Reporting and dashboards

Perform API, UI, and system integration testing across multiple data sources

• Data Quality & Validation
  
  

Ensure accuracy, completeness, and consistency of data powering the “Golden Record”

Validate data pipelines, transformations, and ingestion processes

Perform reconciliation testing across upstream and downstream systems

• AI / GenAI Testing & Validation
  
  

Validate AI-driven Outputs For

Relevance and accuracy of recommendations

Hallucination detection and mitigation

Explainability and traceability (citations, sources)

Design test scenarios for edge cases, bias, and model drift

Collaborate with data scientists to validate ML vs GenAI separation (truth engine integrity)

• Automation & Continuous Testing
  
  

Build and maintain test automation frameworks (UI, API, regression)

Integrate QA into CI/CD pipelines for continuous testing

Enable test data management and reusable test assets

• Performance, Security & Compliance Testing
  
  

Conduct performance and scalability testing for large datasets and concurrent users

Validate security controls and data privacy compliance (especially for client-sensitive data)

Ensure outputs meet fiduciary and regulatory standards (auditability, determinism)