AI QA Specialist

About the job

Our Company We’re Hitachi Digital, a company at the forefront of digital transformation and the fastest growing division of Hitachi Group. We’re crucial to the company’s strategy and ambition to become a premier global player in the massive and fast-moving digital transformation market.

Our group companies, including GlobalLogic, Hitachi Digital Services, Hitachi Vantara and more, offer comprehensive services that span the entire digital lifecycle, from initial idea to full-scale operation and the infrastructure to run it on. Hitachi Digital represents One Hitachi, integrating domain knowledge and digital capabilities, and harnessing the power of the entire portfolio of services, technologies, and partnerships, to accelerate synergy creation and make real-world impact for our customers and society as a whole.

Imagine the sheer breadth of talent it takes to unleash a digital future. We don’t expect you to ‘fit’ every requirement – your life experience, character, perspective, and passion for achieving great things in the world are equally as important to us.

The Team As an AI QA Specialist, you will design and execute test strategies for AI systems, including LLMs, Agentic AI frameworks, and RAG pipelines. You will validate model outputs, monitor AI observability, and enforce governance and compliance standards. Your role ensures that AI solutions meet functional and non-functional requirements before deployment.

The Role AI Testing & Validation

Develop QA frameworks for AI models, multi-agent systems, and orchestration workflows.

Design and execute functional, regression, and performance tests for AI pipelines.

Validate LLM outputs for accuracy, bias, and compliance with enterprise standards.

Observability & Explainability

Implement AI observability dashboards for monitoring latency, reliability, and error rates.

Ensure explainability of AI decisions through evaluation harnesses and reporting tools.

Conduct bias detection, drift monitoring, and safety checks for deployed models.

Automation & Integration

Build automated test suites for AI workflows using Python and CI/CD pipelines.

Integrate QA processes with GCP services (Vertex AI, Cloud Run, GKE) for continuous validation.

Collaborate with engineering teams to embed QA checkpoints into development lifecycle.

Governance & Compliance

Enforce AI safety protocols, data privacy standards, and regulatory compliance.

Document test plans, evaluation metrics, and audit-ready reports.