76 to 100 of 134 Ontologies Jobs

will involve working on enhancements for enriching ADS metadata and practical work including integration of controlled vocabularies and gazetteers, mapping to metadata standards and ontologies, and (meta)data wrangling, cleaning, and transformation. It will include both hands-on work, and an advisory role with regard to current metadata management best ...

high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution in client knowledge Set the design direction for context assembly and memory that manages prompts, context windows ...

data tools. Assess structured and unstructured data to identify anomalies, trends, control weaknesses and emerging risks. Develop and maintain metadata standards, classification models, taxonomies, ontologies and data-labelling structures. Document data lineage, processes, business rules and control frameworks to provide transparency and auditability. Build and operate AI-monitoring controls covering … rules, profiling routines or automated validation controls. Experience working with structured and unstructured datasets. Strong understanding of metadata concepts including classification, lineage, taxonomies and ontology modelling. Knowledge of AI and machine-learning concepts, including model monitoring, drift detection, fairness and bias assessment. Exposure to model validation techniques such as hold ...

build knowledge graph structures that reflect canonical domain models. Develop and manage graph database schemas, queries, and ingestion pipelines, keeping semantic consistency between ontology definitions and downstream data products. Design and implement embedding pipelines that represent Comply’s financial and regulatory data in vector space. Build and operate vector database … ready data products. What success looks like in your first 90 days You’ve shipped your first semantic layer components into production, turning ontology models into working knowledge graph structures. You’ve stood up or extended embedding and vector infrastructure that a consuming team is actively using for semantic search ...

build knowledge graph structures that reflect canonical domain models. Develop and manage graph database schemas, queries, and ingestion pipelines, keeping semantic consistency between ontology definitions and downstream data products. Design and implement embedding pipelines that represent Comply’s financial and regulatory data in vector space. Build and operate vector database … ready data products. What success looks like in your first 90 days You’ve shipped your first semantic layer components into production, turning ontology models into working knowledge graph structures. You’ve stood up or extended embedding and vector infrastructure that a consuming team is actively using for semantic search ...

design, BTP subaccount structure, and Claude model route governance via MCP connector and Skald Gateway. Proven ability to design and govern GraphRAG knowledge planes: ontology and graph edge construction, domain and provenance tagging strategy, trust gate configuration, and citation-enforcement architecture at enterprise scale. Experience leading client-facing technical design ...

design, BTP subaccount structure, and Claude model route governance via MCP connector and Skald Gateway. Proven ability to design and govern GraphRAG knowledge planes: ontology and graph edge construction, domain and provenance tagging strategy, trust gate configuration, and citation‐enforcement architecture at enterprise scale. Experience leading client‐facing technical design ...

foundations that enable Patient Solutions to scale trusted, reusable and AI-ready data across Research and Early Development. You will define and govern metadata, ontologies, identifiers and data standards that improve data quality, interoperability and discoverability. Working across scientific, digital and enterprise teams, you will help shape how data … created, governed and consumed to accelerate research, innovation and AI-driven decision making. What you’ll do Establish and govern enterprise ontologies, business vocabularies and global identifiers to ensure consistent representation and traceability of data across Patient Solutions. Design and implement scalable metadata management capabilities that improve data quality, lineage ...

Work with technical teams to connect AI solutions to governed data sources while preserving access controls, lineage and security Define and maintain metadata and ontology requirements for AI‐enabled analytics, including SharePoint managed metadata, content types, business taxonomy, Microsoft Fabric ontology, OneLake catalog metadata, Power BI semantic model descriptions, glossary ...

layers that give organisations a single, shared and machine-readable understanding of their business. You will work across diverse industries, translating complex domains into ontologies and knowledge graphs that connect data, systems, applications and AI solutions. From discovery and modelling through to production, you will … analytics and generative AI. Responsibilities: Facilitate discovery workshops with business and technical stakeholders to understand and model key domains. Design, build, and maintain scalable ontologies, taxonomies, and semantic models that reflect complex business concepts. Develop and operate knowledge graphs end-to-end, including data ingestion, mapping, and entity resolution pipelines. ...

leadership to enable attack-path analysis, threat investigation, exposure prioritization, GraphRAG , and AI-assisted security operations. Key Responsibilities Design the Security Knowledge Graph architecture, ontology, taxonomy, entity model, relationship model, provenance model, and lifecycle standards. Build production-grade graph ingestion and transformation pipelines for SIEM, EDR/XDR, IAM/… engineers while remaining accountable for prototypes, reference implementations, critical code, troubleshooting, and complex customer or stakeholder demonstrations. Mandatory Hands-on Technical Skills Knowledge graphs: Ontology and semantic model design; property graphs and RDF; graph schema evolution; knowledge representation; provenance; graph quality; entity and relationship resolution. Graph platforms: Deep implementation experience ...

leadership to enable attack-path analysis, threat investigation, exposure prioritization, GraphRAG , and AI-assisted security operations. Key Responsibilities Design the Security Knowledge Graph architecture, ontology, taxonomy, entity model, relationship model, provenance model, and lifecycle standards. Build production-grade graph ingestion and transformation pipelines for SIEM, EDR/XDR, IAM/… engineers while remaining accountable for prototypes, reference implementations, critical code, troubleshooting, and complex customer or stakeholder demonstrations. Mandatory Hands-on Technical Skills Knowledge graphs: Ontology and semantic model design; property graphs and RDF; graph schema evolution; knowledge representation; provenance; graph quality; entity and relationship resolution. Graph platforms: Deep implementation experience ...

SiriusPoint's BI practice from traditional reporting to AI-driven decision intelligence, helping design, build, and govern enterprise analytical datasets, semantic models, and business ontologies that enable scalable self-service analytics and support AI use cases. Leveraging Microsoft Fabric, Power BI, and emerging AI capabilities, you will turn enterprise data … service reporting and analytics, founded on key design principles and a strong focus on user experience. Understanding of semantic layers and knowledge graphs/ontologies as the foundation for AI. Comfort with cloud-based technologies, specifically AWS and Azure. Excellent organizational, written, verbal, and presentation skills. Excellent critical thinking ...

Summary Reporting to the Executive Director, Semantic and Knowledge Engineering, the Associate Director, Semantic and Knowledge Engineering designs, builds, and governs enterprise semantic models, ontologies, taxonomies, business vocabularies, knowledge graphs, metadata services, and semantic APIs. The role enables AI, analytics, enterprise search, interoperability, retrieval-augmented generation (RAG), agentic AI, contextual … require 10% travel. There are 2 positions available. About the Role Key Responsibilities : Enterprise semantic modeling and knowledge engineering • Design, develop, and maintain enterprise ontologies, taxonomies, business vocabularies, and semantic models that establish consistent meaning across products, data, and AI capabilities. • Build and enhance knowledge graphs, metadata services, and semantic ...

leading the transformation of a large, complex data estate into a modern, trusted and value-generating asset, defining the target-state data architecture, ontology and platform strategy that underpins enterprise analytics, AI and digital transformation. You will be a valued member of the Cognizant Consulting team and work collaboratively with … boards and senior stakeholders including CDO, CTO and CIO, and clients. In this role, you will Define and govern the target-state data architecture, ontology, data products, data contracts, and medallion and data mesh architectures across a distributed technology landscape Direct data integration, engineering and pipeline standards, including enterprise-wide ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with end-to-end data pipeline ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value … degree or equivalent, plus all of the following: Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Advanced practical knowledge of schema design, ontology management, and KG curation Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with end-to-end data pipeline ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with end-to-end data pipeline ...

define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value … degree or equivalent, plus all of the following: Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Advanced practical knowledge of schema design, ontology management, and KG curation Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Well versed in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience with ...

define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value … degree or equivalent, plus all of the following: Significant experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Advanced practical knowledge of schema design, ontology management, and KG curation Seasoned in designing and developing KG solutions and graph-based ML models (functional + technical) Proven experience ...