Job Title: Senior Data Architect (Graph & AI/LLM) Location: Mettawa, Illinois, USA
Work Type: Hybrid (Tuesday Thursday onsite)
Employment Type: Contract
Work Environment
Hybrid enterprise environment supporting Commercial Operations initiatives focused on Market Access and Patient Access data solutions. The role involves collaboration with Data Architects, Data Engineers, and AI teams within a large-scale regulated organization.
Role Overview
We are seeking a hands-on Senior Data & Graph Technology Architect to design and deliver an enterprise-grade Knowledge Graph and AI/LLM-enabled platform supporting field teams and downstream commercial operations.
The architect will contribute to building a scalable solution integrating:
- Neo4j-based Knowledge Graph
- LLM/Chatbot interaction layer
- Patient Access and Market Access datasets
- Backend services and metadata systems
- Logging and monitoring frameworks
- Insight delivery interface for business users
This role requires a highly proactive technologist capable of rapidly onboarding, exploring enterprise data independently, and delivering solutions in an agile, MVP-driven environment.
Required Skills & Experience
- 10+ years of enterprise-level Data Architecture experience
- Strong experience working with pharmaceutical or healthcare data
- Expert-level experience with Neo4j / Graph Databases
- Hands-on expertise in:
- Graph Modeling
- Python
- PySpark
- Experience integrating or developing LLM / Chatbot solutions
- Experience building AI-driven enterprise insight platforms
- Strong analytical and problem-solving mindset
- Ability to work independently with minimal supervision
- Experience working in highly regulated environments
Key Responsibilities Knowledge Graph Architecture
- Design and build Neo4j-based knowledge graph models.
- Model complex datasets including patients, coverage, contracts, benefits, and services.
- Optimize graph schemas, relationships, indexing, and query performance.
- Ensure data accuracy, lineage, and compliance alignment.
AI / LLM Integration
- Develop chatbot and LLM-powered workflows integrated with the knowledge graph.
- Implement Retrieval-Augmented Generation (RAG) approaches.
- Perform prompt engineering and domain-specific optimization.
- Align AI components with enterprise governance and compliance standards.
Backend & Data Engineering
- Develop backend services integrating graph and AI systems.
- Build logging and metadata frameworks using cloud technologies.
- Develop ETL/ELT pipelines ingesting enterprise data sources.
- Support scalable and maintainable data architecture patterns.
Domain Data Modeling
- Analyze and model Market Access and Patient Access datasets including:
- Coverage and payer data
- Contracting and rebate structures
- Access and affordability programs
- Gross-to-Net (GTN) components
- Translate business context into accurate graph relationships.
Agile Delivery
- Deliver iterative MVP progress within agile workflows.
- Participate in standups, architecture reviews, and sprint planning.
- Own deliverables end-to-end from design through deployment.
- Proactively identify risks, gaps, and improvement opportunities.
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