Job Title: Data Scientist – GenAI & Knowledge Graphs Location: Seattle, WA, US Employment Type: Full-time Job Summary We are hiring a Data Scientist to support the development of Generative AI applications that leverage knowledge graphs, GraphDBs, and multi-agent orchestration. This role is hands-on, focused on practical implementation of GenAI patterns using state-of-the-art open-source libraries and graph technologies. Key Responsibilities • Develop graph data models using Neo4j, RDF, and SPARQL/Cypher for building semantic knowledge representations. • Support the design and enrichment of ontologies using OWL and Protégé, aligning data schemas for GenAI use cases. • Build components of agentic AI systems using frameworks like LangGraph, CrewAI, or AutoGen under senior guidance. • Assist in implementing RAG pipelines, working with vector databases and embedding models for improved document search. • Implement agent-to-agent (A2A) interaction flows and agent memory structures in prototype-level applications. • Work with Python, integrating APIs from LLM providers (OpenAI, Anthropic, etc.) with knowledge graph backends. • Maintain documentation, test cases, and reusable code modules for internal projects. Required Skills & Experience • 2–4 years of experience in data science or NLP/ML roles. • Exposure to GraphDBs like Neo4j or Neptune and basic query languages like Cypher or SPARQL. • Understanding of ontology basics, OWL standards, and tools like Protégé. • Familiarity with GenAI tools and libraries (LangChain, LangGraph, CrewAI, etc.). • Strong Python skills with ability to work with REST APIs, LLM SDKs, and embedding models. • Good documentation, debugging, and collaboration skills. Preferred Qualifications • Bachelor’s degree in Data Science, Computer Science, or related field. • Familiarity with agent protocols (MCP, A2A) and experience participating in GenAI POCs or hackathons. • Interest in growing expertise in semantic AI, graph-based ML, and agentic systems.