Description

Key Responsibilities:

• AI use cases such as mapping recommendations, duplicate/orphan detection, match explanation, DQ anomaly detection, impact analysis and natural-language discovery.
• Define AI architecture, model selection, data access, prompt/context patterns, evaluation and MDM/RDM integration.
• Design human-in-the-loop controls so AI never changes authoritative master/reference data without approved governance.
• Define evidence and explainability for match, mapping and DQ recommendations.
• Set AI privacy/security controls for PHI/PII, access, logging, retention and data minimisation.
• Define evaluation datasets, accuracy thresholds, drift monitoring and production quality controls.
• Lead AI proof-of-concept and transition successful use cases into governed production services.

Primary Deliverables:

• AI use-case portfolio and prioritisation
• AI reference architecture
• AI governance / guardrail specification
• Evaluation framework and benchmark results
• Pilot / production integration design
• AI monitoring and operating model

Required Experience & Skills:

8+ years in AI/ML architecture, including enterprise generative and agentic patterns. Strong data architecture background and integration with data workflows. Experience deploying approved models with human-in-the-loop controls.

Good to Have:

Responsible AI and regulated data experience. Vertex AI or equivalent on Google Cloud Platform. MLOps and model monitoring

Key Skills

Education

Any Graduate