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, ensuring a smooth handoff from CoE to Engineering.
Support the AI Engineering Committee (AIEC) by documenting architectural fit and identifying potential technical debt in proposed solutions.
Monitor and aggregate telemetry data on token usage, cost, and error rates to support the 'Value Analyst' in ROI reporting.
Assist in the creation of 'Data Dictionaries' and 'Knowledge Graphs' required to ground RAG (Retrieval Augmented Generation) pipelines.
Validate that yellow layer automations (UiPath, Databricks) utilize approved MCP connectors and do not bypass API gateways.
Collaborate with Data Governance to tag and classify datasets specifically approved for LLM training or fine-tuning.
Track the lifecycle of AI models from 'Pilot' to 'Production' to 'Retirement' in the enterprise inventory system.
Support the configuration of 'Model Routers' by analyzing performance benchmarks across different LLMs (GPT-4 vs. Llama) for specific tasks.
Create process flow diagrams for 'Agentic Workflows' to visualize how multiple agents interact and hand off tasks.
Perform any other job related duties as requested.

Requirements

Bachelor's degree in Information Systems, Computer Science, Data Analytics, or related field required
Equivalent years of relevant work experience may be accepted in lieu of required education
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.

Benefits

Base compensation and potential for bonuses tied to company and individual performance
Substantial and comprehensive total rewards package

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data analysistechnical feasibility analysisdata lineage assessmentdata quality assessmentAPI integrationdata governancemodel performance analysisprocess flow diagram creationRAG pipelinesautomation with UiPath

Soft Skills

collaborationdocumentationcommunicationorganizational skillsproblem-solving