Senior AI Graph DBX Developer

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We are looking for a Senior AI Graph DBX Developer to join our advanced agentic AI engineering team. You will play a pivotal role in building knowledge-driven AI systems that power autonomous agents across diverse business workflows. You’ll work on next-generation agentic frameworks and platforms including Kodosumi, Masumi, and Sokosumi, designing the intelligence backbone that enables agents to reason, collaborate, and act autonomously.

This role sits at the intersection of Graph Databases, Knowledge Graphs, LLMs, and Agentic AI—ideal for engineers passionate about building intelligent systems at scale.

Responsibilities:

Knowledge Architecture & Design

• Design and implement scalable knowledge graphs and knowledge bases as core intelligence layers
• Architect graph-based representations for complex business domains and evolving knowledge structures

Graph Database Engineering

• Build, optimize, and manage graph databases using Neo4j, Amazon Neptune, ArangoDB, TigerGraph, or similar
• Design efficient graph schemas and implement graph traversal and query optimization strategies
• Ensure high-performance graph operations for real-time AI workflows

GraphRAG & LLM Integration

• Develop GraphRAG (Graph Retrieval-Augmented Generation) systems
• Combine vector embeddings with graph relationships for richer LLM context
• Integrate graph databases with modern LLM architectures for intelligent knowledge retrieval

Agentic Workflow Enablement

• Implement graph-based reasoning to support multi-agent collaboration
• Design persistence and retrieval patterns for agent learning and memory
• Enable decision-making across complex, multi-step business scenarios

Performance & Scalability

• Optimize graph databases for high-throughput, concurrent agent operations
• Implement caching and distributed graph architectures
• Design systems that scale with growing knowledge bases and agent populations

Required Qualifications:

Graph & Knowledge Systems

• 5+ years of hands-on experience with graph databases
• Strong foundation in graph theory, algorithms, and data modeling
• Proven experience building enterprise-scale knowledge graphs
• Proficiency in Cypher, Gremlin, SPARQL

AI & LLM Integration

• Solid understanding of Large Language Models (LLMs)
• Hands-on experience with GraphRAG, vector databases, and hybrid retrieval
• Knowledge of RDF, semantic web technologies, and ontology engineering
• Familiarity with agent-based and multi-agent architectures

Development & Platform Skills

• Strong proficiency in Python
• Experience with graph visualization tools
• Understanding of distributed systems and microservices
• Familiarity with Docker, Kubernetes, and cloud platforms

Good to Have

• Experience building agentic AI systems or autonomous agents
• Background in knowledge representation, semantic reasoning, or expert systems
• Contributions to open-source graph or AI projects
• Experience with real-time streaming data and dynamic knowledge graph updates
• Understanding of business process modeling and workflow orchestration