AI Architect - Enterprise Semantic Solution
Compunnel, Spring, TX, United States
Job Summary:
We are seeking an experienced AI Architect to lead the design and implementation of an enterprise semantic layer that enables business users to interact with structured and unstructured data through natural language and chat-based experiences. This role focuses on building a unified data consumption layer, defining semantic models, and establishing a scalable enterprise architecture that connects data across multiple business domai ns.
Key Responsibilities:
Architect and implement an enterprise semantic layer to enable natural language interaction with curated data products. Define and develop an enterprise context layer that connects multiple semantic implementations across domains. Design and support a central data consumption layer and curated data product strategy. Collaborate with business and technical stakeholders to define ontology models, semantic structures, and governance standards. Translate high-level architectural concepts into actionable implementation plans and deliverables. Contribute to layered semantic architecture including modeling, ontology extraction, curated semantic views, and enterprise connectivity. Work across cloud data platforms, cataloging tools, graph technologies, and orchestration frameworks. Establish reusable frameworks for semantic information orchestration and enterprise data consumption. Required Qualifications:
Proven experience designing and implementing enterprise semantic layers or semantic orchestration solutions. Hands-on experience with semantic technologies, LLM frameworks, and graph technologies such as Neo4j. Experience working with Snowflake and Collibra. Strong understanding of enabling natural language and chat-based interaction with structured and unstructured data. Experience defining ontology models, semantic structures, and enterprise information architecture. Ability to translate architectural vision into practical implementation outcomes. Experience working across multiple platforms and business domains. Strong collaboration and stakeholder management skills. Preferred Qualifications:
Experience with modern cloud data platforms used as centralized data hubs. Familiarity with enterprise data cataloging and governance tools. Experience with graph and non-graph approaches for semantic integration. Exposure to enterprise data marketplace and reusable AI/semantic frameworks.
We are seeking an experienced AI Architect to lead the design and implementation of an enterprise semantic layer that enables business users to interact with structured and unstructured data through natural language and chat-based experiences. This role focuses on building a unified data consumption layer, defining semantic models, and establishing a scalable enterprise architecture that connects data across multiple business domai ns.
Key Responsibilities:
Architect and implement an enterprise semantic layer to enable natural language interaction with curated data products. Define and develop an enterprise context layer that connects multiple semantic implementations across domains. Design and support a central data consumption layer and curated data product strategy. Collaborate with business and technical stakeholders to define ontology models, semantic structures, and governance standards. Translate high-level architectural concepts into actionable implementation plans and deliverables. Contribute to layered semantic architecture including modeling, ontology extraction, curated semantic views, and enterprise connectivity. Work across cloud data platforms, cataloging tools, graph technologies, and orchestration frameworks. Establish reusable frameworks for semantic information orchestration and enterprise data consumption. Required Qualifications:
Proven experience designing and implementing enterprise semantic layers or semantic orchestration solutions. Hands-on experience with semantic technologies, LLM frameworks, and graph technologies such as Neo4j. Experience working with Snowflake and Collibra. Strong understanding of enabling natural language and chat-based interaction with structured and unstructured data. Experience defining ontology models, semantic structures, and enterprise information architecture. Ability to translate architectural vision into practical implementation outcomes. Experience working across multiple platforms and business domains. Strong collaboration and stakeholder management skills. Preferred Qualifications:
Experience with modern cloud data platforms used as centralized data hubs. Familiarity with enterprise data cataloging and governance tools. Experience with graph and non-graph approaches for semantic integration. Exposure to enterprise data marketplace and reusable AI/semantic frameworks.