Analyze incoming AI use cases to determine technical feasibility, data availability, and appropriate risk tiering (green/yellow/red)
Perform detailed data lineage and quality assessments to ensure training/RAG datasets meet governance standards for accuracy and PII/PHI protection
Maintain the 'AI Agent Registry & Catalog,' documenting agent capabilities, API dependencies, and ownership within the Azure APIM and Mesh architecture
Draft technical requirements and 'Definition of Ready' artifacts for the Platform Engineering team
Support the AI Engineering Committee (AIEC) by documenting architectural fit and identifying potential technical debt in proposed solutions
Track the lifecycle of AI models from 'Pilot' to 'Production' to 'Retirement' in the enterprise inventory system
Requirements
Bachelor's degree in Information Systems, Computer Science, Data Analytics, or related field required
Five (5) years in Systems Analysis, Data Analysis, or Technical Product Ownership required
Experience documenting technical requirements for data-intensive applications, API integrations, or cloud platforms required
Background in Healthcare Payer data (Claims, Member, Provider) is preferred
Proficiency in SQL and data profiling
Understanding of API specifications (REST/JSON) and microservices architecture