Senior Technical Architect

AI Architect

Location: Chicago, IL – Hybrid (3 days/week onsite)

Job Type: Contract

Experience: 12–15 Years

Job Summary

We are seeking an experienced AI Architect to design and lead the architecture of next-generation Agentic AI, Generative AI, Machine Learning, and Knowledge Graph solutions for healthcare applications.

The ideal candidate will have strong expertise in Agentic AI, Knowledge Graph, Stardog, ML, RAG, and enterprise data architecture, along with an understanding of healthcare data, HIPAA, PHI, EHR/Epic, FHIR, and HL7.

The AI Architect will work closely with engineering, data, AI/ML, and business teams to define scalable, secure, and production-ready solutions.

Key Responsibilities

• Define end-to-end Agentic AI and Knowledge Graph architecture for enterprise healthcare applications.
• Design supervisor, planner, specialized agent, tool-use, and human-in-the-loop patterns.
• Define integrations with VIP Data Platform, Orkes workflows, Azure Databricks, and Unity Catalog.
• Design and develop Stardog Knowledge Graph models, including schemas, mappings, recipes, rules, lineage, and contractual controls.
• Establish AI security and governance standards covering HIPAA, PHI protection, tenant isolation, and data/contract compliance.
• Define standards for grounding, explainability, confidence scoring, AI evaluation, and observability.
• Guide the development of reusable AI agent capabilities for source discovery, Epic mapping, recipe generation, data quality, and remediation.
• Review solution architecture, technical designs, implementation deliverables, and production readiness.
• Collaborate with engineering and data teams to ensure architecture standards are consistently followed.
• Provide technical leadership and architectural guidance throughout the solution lifecycle.

Required Skills & Qualifications

• 12–15 years of experience in enterprise architecture, AI/ML, data platforms, or related technology domains.
• Strong experience designing Agentic AI / Generative AI / ML architectures.
• Hands-on experience with Knowledge Graph technologies, ontology, semantic modeling, and graph-based retrieval.
• Strong experience with Stardog.
• Experience designing multi-agent orchestration and human-in-the-loop architectures.
• Strong understanding of RAG and hybrid retrieval using graph, vector, and structured data.
• Experience with healthcare data, EHR/Epic, clinical data integration, HIPAA, and PHI.
• Understanding of data engineering, metadata management, data lineage, and data quality.
• Strong knowledge of API, microservices, event-driven architecture, security, and cloud architecture.
• Excellent communication, stakeholder management, technical leadership, and architecture governance skills.

Technology Stack

• AI/GenAI: Agentic AI, Generative AI, ML, RAG, Hybrid RAG
• AI Platforms: Azure AI Foundry, LangChain, DeepAgents
• Knowledge Graph: Stardog, Ontology, Semantic Modeling
• Workflow/Orchestration: Orkes
• Data Platform: Azure Databricks, PySpark, Unity Catalog, MLflow
• Azure: Azure Blob Storage, Azure Document Intelligence
• Observability: Dynatrace, OpenTelemetry
• Development: Python, SQL, REST APIs, Microservices
• Healthcare: FHIR, HL7, EHR/Epic
• DevOps: GitHub, CI/CD

Mandatory Skills

• Stardog
• Agentic AI
• Knowledge Graph
• Machine Learning (ML)

Preferred Qualifications

• Experience architecting AI solutions within healthcare or regulated environments.
• Experience with Azure cloud and Databricks.
• Experience with Epic, FHIR, and HL7.
• Relevant technical certifications in AI/ML, Cloud, Data, or Architecture are a plus.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.