AI Architect

VeeRteq Solutions Inc.

  • Chicago, IL
  • 7 days ago

    Highlights

    Azure AI Foundry, LangChain, DeepAgents, Stardog, Orkes, Azure Databricks and PySpark, MLflow Unity Catalog Azure Blob Storage Azure Document Intelligence Dynatrace and OpenTelemetry GitHub and CI/CD Python, SQL, REST APIs, FHIR, HL7. Design the Stardog Knowledge Graph model for schemas, mappings, recipes, rules, lineage, and contractual controls.

    Numbers & Facts

    LocationChicago, IL

    Description

    Job Title: AI Architect

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

    Experience: - 12-15 Years

    Mandatory skills

    Stardog, Agentic AI, Knowledge Graph, ML

    As an AI Architect, you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards.

    Responsibilities: -

    Define the end-to-end Agentic AI and Knowledge Graph architecture.

    Design supervisor, planner, specialized agent, tool-use, and human-in-the-loop patterns.

    Define integration with VIP data platform, Orkes workflows, Databricks, and Unity Catalog.

    Design the Stardog Knowledge Graph model for schemas, mappings, recipes, rules, lineage, and contractual controls.

    Establish AI security, HIPAA, PHI protection, tenant isolation, and contract-honoring guardrails.

    Define standards for grounding, explainability, confidence scoring, evaluation, and observability.

    Guide reusable agent skills for source discovery, Epic mapping, recipe generation, quality, and remediation.

    Review solution designs, technical deliverables, and production-readiness.

    Skills Required

    Enterprise architecture for Agentic AI, GenAI, ML, and data platforms.

    Multi-agent orchestration and human-in-the-loop architecture.

    Knowledge Graph, ontology, semantic modeling, and graph-based retrieval.

    RAG and hybrid retrieval using graph, vector, and structured data.

    Healthcare data, HIPAA, PHI, EHR/Epic, and clinical-data integration knowledge.

    Data engineering, metadata management, lineage, and data-quality concepts.

    API, microservices, event-driven, security, and cloud architecture.

    Strong stakeholder communication and architecture-governance skills.

    Tool & Technology Exposure

    Azure AI Foundry, LangChain, DeepAgents, Stardog, Orkes, Azure Databricks and PySpark, MLflow Unity Catalog Azure Blob Storage Azure Document Intelligence Dynatrace and OpenTelemetry GitHub and CI/CD Python, SQL, REST APIs, FHIR, HL7

    Educational Qualifications: -

    • Engineering Degree BE/ME/BTech/MTech/BSc/MSc.

    Technical certification in multiple technologies is desirable.

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