AI Systems Architect

Hello, Hope you are doing well. This is OpenKyber from OpenKyber. Kindly find the below job description and let me know your availability Position: Knowledge Graph Architect AI & Graph Analytics Platforms Location: Remote Duration: 12+ months contract Job Description: Core Expertise Requirements: Hands-on experience in building, deploying, and scaling enterprise Knowledge Graph (KG) platforms in production environments. Demonstrated experience operating KGs at scale with a deep understanding of performance optimization, scalability challenges, and operational lessons learned from production deployments. Strong experience in designing and implementing ontology layers and semantic models for Knowledge Graphs. Deep understanding of ontology design, schema evolution, and how semantic constructs support scalability, reasoning, and maintainability of large graph ecosystems. Domain experience in Knowledge Graph development within Supply Chain ecosystems including supplier networks, product relationships, and operational dependencies. Healthcare domain exposure will be considered an added advantage. Key Responsibilities: Enterprise Knowledge Graph Architecture: Define and implement enterprise-scale Knowledge Graph architecture representing entities, relationships, dependencies, and business context. Design semantic models, ontologies, and graph schemas for enterprise data ecosystems. Establish standards, governance frameworks, and best practices for Knowledge Graph adoption across the organization. Design scalable ontology-driven graph architectures that support long-term extensibility and reasoning capabilities. Technology Architecture: Graph Databases: Lead architecture and evaluation of enterprise graph platforms: Amazon Neptune, Neo4j, ArangoDB Graph Data Models RDF (Resource Description Framework), Labeled Property Graph (LPG) Graph Query Languages Cypher, SPARQL, Gremlin, ArangoQL AI & LLM Ecosystem: Experience designing AI platforms using: LLM Platforms: OpenAI / Azure OpenAI, Anthropic Claude LLM Frameworks: LangChain, LangGraph, LlamaIndex Data & Platform Engineering: Snowflake, Python / Java / Scala, Data engineering pipelines, ETL / ELT frameworks, Integration with data lake / lakehouse platforms, APIs and microservices for AI applications Cloud Platforms: AWS (preferred for Neptune-based architectures) Required Skills: Deep expertise in Knowledge Graph architecture and semantic modeling Strong background in graph theory and network analytics Enterprise architecture experience for AI-driven platforms Graph analytics algorithms (centrality, clustering, similarity, link prediction) Graph traversal and path analysis Knowledge Graph integration with LLM and GraphRAG architectures Strong background in data engineering and distributed data platforms Preferred Experience: Enterprise Knowledge Graph implementations Graph-based supply chain or ecosystem analytics platforms AI copilots and enterprise knowledge assistants Graph-based decision intelligence platforms Experience with Graph Data Science libraries Education: Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, Applied Mathematics Ideal Candidate A technology leader with deep expertise in Knowledge Graphs, Graph Analytics, and AI architectures, capable of designing next-generation GraphRAG platforms that combine. Knowledge Graph intelligence with LLM-based reasoning to enable enterprise decision intelligence and advanced analytics across complex networked systems. For applications and inquiries, contact: hirings@openkyber.com