AI Systems Analyst III

• 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.

• Bachelor's degree in Information Systems, Computer Science, Data Analytics, or related field required 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

• Proficiency in SQL and data profiling, capable of analyzing datasets for quality, lineage, and PII/PHI exposure
• Understanding of API specifications (REST/JSON) and microservices architecture to document agent dependencies
• Ability to translate business needs into technical user stories and "Definition of Ready" criteria for engineering teams
• Familiarity with Data Governance tools (e.g., Purview, Collibra) and metadata management
• Knowledge of RAG (Retrieval Augmented Generation) concepts to help define knowledge base requirements

• CBAP (Certified Business Analysis Professional) or PMI-PBA preferred
• Azure Data Fundamentals certification preferred

• General office environment; may be required to sit or stand for extended periods of time
• Travel is not typically required

Compensation Range:

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.