AI Systems Analyst III at CareSource

Dayton, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Jul, 26

Salary

164800.0

Posted On

12 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Systems Analysis, Data Analysis, Technical Product Ownership, SQL, Data Profiling, API Specifications, Microservices Architecture, Data Governance, Metadata Management, RAG, Azure APIM, Data Lineage, Technical Requirements Documentation, Process Flow Diagrams, Performance Benchmarking

Industry

Insurance

Description

Job Summary: The AI Systems Analyst III provides the technical and analytical rigor behind the intake and triage process. Working within the CoE, this role analyzes business requirements against technical capabilities, ensuring that data readiness, lineage, and architectural fit are validated before a project enters the build phase. They maintain the enterprise AI Registry, serving as the librarian of the AI Mesh. Essential Functions: 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. Education and Experience: 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 Competencies, Knowledge and Skills: 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 Licensure and Certification: CBAP (Certified Business Analysis Professional) or PMI-PBA preferred Azure Data Fundamentals certification preferred Working Conditions: General office environment; may be required to sit or stand for extended periods of time Travel is not typically required Compensation Range: $94,100.00 - $164,800.00 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): 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. #LI-GM1 The CareSource mission is known as our heartbeat. Just as we support our members to be the best version of themselves, our employees are driven by our mission to create a better world for members, stakeholders and providers. We are difference-makers who combine compassionate hearts with our unique business expertise to make every opportunity count. Each claim, each phone call, each consumer-centric decision is a chance to change the world for one member, and our employees look for ways to do that every day. The challenge is, there is no one right way to be the difference and we’re looking for people like you that will rewrite that definition every day. We do what it takes to form creative solutions that make our community and the world just a little better. Discover what it means to be #UniquelyCareSource.

Responsibilities

The AI Systems Analyst III manages the intake and triage of AI use cases while maintaining the enterprise AI Registry and Mesh architecture. They validate technical feasibility, data readiness, and architectural fit to ensure smooth handoffs to the Platform Engineering team.