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Lead the enterprise AI strategy and architecture, AI Innovation Lab, and a distributed team of AI architects and engineers across US and GCC locations.

Compensation

The anticipated base pay range for this position is : $140,000.00 - $241,500.00

Responsibilities

Define and evolve the enterprise AI strategy, architecture and roadmap
Architect the agentic runtime and related services
Design reusable context and knowledge services
Establish patterns for LLMOps and MLOps
Create a discoverable catalog of AI services

Requirements

Bachelor's degree in Computer Science, Engineering or a related technical field
Nice to have: Accessible Design
Nice to have: Agility Jumps
Nice to have: Business Alignment
Nice to have: Cloud Computing

Skills

LLM integration multi-agent orchestration RAG Graph RAG tool calling MCP/A2A

Ontology FDO

Synechron · Posted Nov 9, 2026

Open

Glasgow, Scotland, United Kingdom

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Graph Engineer / Ontologist to design, develop, and implement enterprise knowledge graphs and semantic data solutions in a regulated financial‑services environment.

Responsibilities

Design and develop knowledge graphs, ontologies, taxonomies, and semantic information models
Translate business, operational, financial, and regulatory requirements into formal graph and ontology specifications
Define entities, relationships, attributes, constraints, classifications, and semantic rules
Develop graph data models using RDF, OWL, SKOS, SHACL, SPARQL, property‑graph models and Cypher
Build data‑mapping and ingestion processes from relational databases, APIs, documents, and other enterprise data sources

Requirements

Relevant degree or equivalent experience in computer science, information systems, data science, mathematics, engineering, or a related field
Nice to have: Experience in banking, capital markets, financial services, risk, compliance, or regulatory data
Nice to have: Knowledge of financial‑industry standards and reference models such as FIBO, ISO 20022, LEI
Nice to have: Experience with data lineage, metadata management, master data management, data catalogues, or data governance
Nice to have: Familiarity with cloud platforms, containerisation, CI/CD, and infrastructure‑as‑code

Skills

Graph engineering Ontology development Semantic modelling Knowledge representation Data modelling principles Information architecture RDF OWL SKOS SHACL SPARQL Neo4j Amazon Neptune Stardog GraphDB AllegroGraph

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Senior Knowledge Graph & Ontology Architect

Cognizant · Posted Nov 10, 2026

Open

Remote, United States
Remote
Full-time · Senior
$130K–$160K per year
8+ years

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Design and govern enterprise semantic architectures, ontologies, and knowledge graph platforms to enable AI-ready knowledge systems.

Compensation

The annual salary for this position is between $ 130,000 - $ 160,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Responsibilities

Design and govern enterprise ontologies, semantic models, and knowledge graph architectures
Lead development of business domain models and governed vocabularies
Define and maintain enterprise business glossaries, KPI registries, and governance processes
Architect graph-based knowledge platforms using technologies such as Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, GraphDB, Dataplex, BigQuery, and Vector Search
Partner with engineering, AI, and platform teams to establish governance controls, security standards, and AI architecture guardrails

Requirements

Nice to have: Spanner Graph GQL
Nice to have: knowledge architecture for agentic AI
Nice to have: retrieval-augmented generation
Nice to have: Vertex AI
Nice to have: Gemini

Skills

OWL/RDF ontology development semantic modeling

GCP data Engineer

Cognizant · Posted Nov 8, 2026

Open

Remote, United States
Remote
Full-time
$100K–$120K per year
5+ years

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Build and operate connectivity, profiling, and graph/search foundation for enterprise ontology and knowledge management platforms.

Compensation

The annual salary for this position is anticipated to be between $100,000 and $120,000 USD, depending on experience, qualifications, geographic location, and other factors permitted by law.

Responsibilities

Transform raw operational and master data sources into clean, lineage-tracked, governed, and queryable knowledge assets
Design and support data connectivity, metadata management, graph platforms, ingestion frameworks, and search capabilities
Build adapters and integration frameworks for BigQuery, Cloud SQL, REST APIs, Apigee, GCS, Pub/Sub
Establish scalable ingestion patterns for operational, transactional, and master data systems
Support API-based integrations across enterprise applications and data platforms

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related discipline
Nice to have: Spanner Graph
Nice to have: Telecommunications environments
Nice to have: OSS/BSS Systems
Nice to have: TM Forum SID

Skills

Python SQL Google Cloud Platform

Data Scientist - Graph Neural Networks

ApTask · Posted Nov 6, 2026

Open

Remote, United States
Remote
Contract · Senior
7–12 years

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We are seeking a highly skilled Data Scientist with proven expertise in Graph Neural Networks (GNNs) and Graph Machine Learning to lead the design, development, and implementation of graph-based AI models as part of a strategic Proof of Concept (POC).

Responsibilities

Design, build, and optimize Graph Neural Network (GNN) models for complex business problems.
Develop graph-based solutions for Link Prediction, Node Classification, Recommendation Systems, Network Analysis, Knowledge Graph Analytics, Fraud Detection, and Entity Resolution.
Build scalable graph data pipelines and feature engineering workflows.
Conduct model evaluation, experimentation, and performance optimization.
Collaborate with domain experts, architects, and engineering teams to deliver production-ready solutions.

Requirements

Nice to have: Neo4j
Nice to have: TigerGraph
Nice to have: Amazon Neptune
Nice to have: JanusGraph
Nice to have: NetworkX

Skills

Graph Neural Networks (GNN)Graph Convolution Networks (GCN)Graph Attention Networks (GAT)GraphSAGE

Knowledge Engineer / Semantic Expert for AI

Accenture Infrastructure and Capital Projects, LLC · Posted Nov 5, 2026

Open

California, United States +13 more
Full-time
$74K–$220K per year
12+ years

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Lead and develop Knowledge Graph solutions, design AI and semantic solutions, collaborate with cross-functional teams, justify value of semantic layer to clients, support sales efforts, and stay current on emerging AI technologies.

Locations (14)

California, United States
Colorado, United States
Connecticut, United States
District of Columbia, United States
Illinois, United States

Staff Backend Graph Engineer

Socure · Posted Nov 5, 2026

Open

Remote, United States
Remote
Full-time · Staff
7+ years

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Build the graph that decides who’s real, setting the technical direction for the platform behind identity decisions, owning entity resolution at scale, and leading architecture decisions.

Responsibilities

Shape the graph. Define the schemas, relationships, and ontology that make identity data consistent and extensible.
Own entity resolution at scale across messy, sparse, and adversarial data.
Design batch and real-time pipelines, low-latency APIs, and serving systems.
Power fraud intelligence by shipping production systems for ML features, model inference, and graph analytics.
Improve performance, reliability, and cost.

Requirements

Bachelor’s degree in Computer Science
Master’s degree in Computer Science
Data Engineering related field
Nice to have: Distributed systems
Nice to have: Low-latency serving

Skills

Java Scala Python Spark Kafka Flink

Senior Semantic Data & Knowledge Engineer

Novartis · Posted Nov 5, 2026

Open

Hyderabad, Telangana, India
Hybrid
Senior
5+ years

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Design, implement, and maintain enterprise knowledge structures, ontologies, semantic assets, metadata frameworks, knowledge graphs, and business glossaries to support analytics, AI, GenAI, semantic search, and agentic AI use cases.

Responsibilities

Develop and maintain ontologies, taxonomies, semantic models, and business glossaries
Define relationships between business concepts, policies, controls, processes, and data assets
Build and maintain enterprise knowledge graphs and semantic repositories
Translate business knowledge into AI-ready semantic structures
Support standardization of enterprise business terminology

Requirements

Bachelor's or Master's degree in Information Management, Computer Science, Data Science, Analytics, AI, or related field
Nice to have: Microsoft Fabric
Nice to have: Amazon Neptune
Nice to have: Collibra
Nice to have: Metadata Management

Skills

AWS Data Platforms Knowledge Graphs Ontology Development Taxonomy Design RAG / GraphRAG

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