Job Description
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.
Job Tags
Full time,