Principal Test AI Engineer

Principal AI Test Engineer plays a critical role in shaping and advancing IDBS’s AI test strategy across our engineering organization.

• AI Quality Strategy & Governance:
  Own and define end-to-end testing strategy for AI/ML systems, establishing standards for model quality, robustness, fairness, explainability, and regulatory compliance across the organization.
• Advanced Validation & Risk Assessment:
  Design and lead sophisticated validation approaches for AI models and data pipelines, including bias detection, drift monitoring, adversarial testing, and failure‑mode analysis in production environments.
• Test Architecture & Automation Leadership:
  Architect scalable, automated test frameworks for AI systems (models, data, pipelines, and integrations), leveraging MLOps, CI/CD, synthetic data, and observability tooling.
• Technical Leadership & Mentorship:
  Act as the subject‑matter expert for AI testing, mentoring engineers, influencing engineering best practices, and partnering closely with data science, platform, legal, and product teams.
• Stakeholder Influence & Continuous Improvement:
  Translate complex AI risks and quality metrics into clear insights for senior stakeholders, shaping product decisions and continuously improving AI quality, reliability, and trustworthiness at scale.

• High-quality level of testing of our AI systems, within specific teams and then across the organization.
• AI applications that are consistent, robust, fair, explainable and observable, delivering results customers expect.
• Test outcomes that are transparent, highly visible, immediately available, and acted on, integrated into the SDLC and automated release process.
• Continued expansion and excellence in the breadth, depth, and quality of our AI product portfolio.
• Full confidence from the wider organization and customers in our AI products and the results they produce.

• Testing AI/ML systems is a must.
• Automating AI testing and a good knowledge of other testing forms and working in an Agile environment.
• A background in influencing standards and practices across multiple teams without direct line management responsibility.