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Programm ers.io is seeking a Senior Neo4j Knowledge Graph Architect for a remote, full-time role. You will lead performance tuning and graph data modeling to support AI-driven discovery and contextual retrieval across large-scale graph environments.
You will also architect enterprise knowledge assets, optimize Cypher queries, and oversee graph operations, memory management, and data ingestion pipelines in a production setting.
Position: Senior Neo4j Knowledge Graph Architect
Location: Remote
Hire Type: Full Time
Job Summary:
Looking for a Senior Neo4j Knowledge Graph Architect with strong Cypher query tuning, graph data modeling, indexing, and performance engineering experience to analyze and reduce Neo4j query response times.
Desired Skill Profile (Priority Areas)
1. Neo4j Performance Tuning Expert
Deep experience with Neo4j query optimization, execution plans (PROFILE/EXPLAIN), indexing strategies, and query latency reduction.
Proven track record diagnosing and resolving performance bottlenecks in large-scale graph environments
2. Knowledge Graph Architect
Strong expertise in graph data modeling, ontology/relationship design, traversal patterns, and scalable knowledge graph architectures.
Experience designing enterprise knowledge assets that support AI-driven discovery and contextual retrieval
3. Cypher Query Specialist
Hands-on experience writing and optimizing complex Cypher queries.
Ability to identify inefficient graph traversals, optimize query patterns, and improve overall graph performance.
4. Graph Database Operations & Monitoring
Expertise in Neo4j operational management, including memory management, page cache tuning, heap sizing, cluster performance, monitoring, and capacity planning.
Strong background in data engineering, ingestion pipelines, graph analytics, and operating graph platforms at enterprise scale.
Experience integrating multiple structured and unstructured data sources into knowledge graph ecosystems.
Additional Skill Requirement
AI-led SDLC Engineering experience, including practical application of GenAI, Agentic AI, RAG, developer productivity platforms, and AI-assisted software engineering workflows.