Overview
Skills
Job Details
HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Senior Data Scientist GenAI & Knowledge Graphs in Seattle, WA. Below is the detailed job description.
Title: Senior Data Scientist GenAI & Knowledge Graphs
Location: Seattle, WA, US
Full-time
Job Description:
We are looking for a Senior Data Scientist with hands-on expertise in building Generative AI applications using Knowledge Graphs, Graph Databases, and multi-agent systems. The ideal candidate will have strong experience in LLM-driven development, agentic AI workflows, and semantic data modeling using OWL and RDF. Key Responsibilities Build and maintain graph-based data pipelines using technologies like Neo4j, Amazon Neptune, or Stardog. Design and implement knowledge graphs and ontologies using OWL, Prot g , TopBraid, or similar tools. Integrate knowledge graphs with GenAI pipelines, improving context grounding and retrieval for LLM-based applications. Develop and orchestrate multi-agent systems using LangGraph, CrewAI, or AutoGen, including agent-to-agent (A2A) communication, memory modules, and reasoning chains. Leverage MCP servers and agent runtime engines to deploy agent-based GenAI applications for real-world scenarios such as customer support, content synthesis, and document analysis. Work on RAG architectures involving embedding models, vector stores (e.g., FAISS, Pinecone), and structured semantic layers. Collaborate with engineers and junior data scientists on project delivery and model deployment. Write clean, reusable code in Python using ML/LLM frameworks such as LangChain, HuggingFace, and OpenAI SDKs.
Required Skills & Experience 5 8 years of experience in data science, with 2+ years in LLM/GenAI development. Hands-on experience with GraphDBs (Neo4j, Neptune, TigerGraph) and SPARQL or Cypher. Proficiency in ontology modeling using OWL/RDF and familiarity with semantic reasoning tools. Strong experience in building agentic AI applications, including use of LangGraph, AutoGen, or CrewAI. Understanding of multi-agent communication protocols (A2A), agent memory, and orchestration layers. Solid understanding of data wrangling, NLP, and embedding models (sentencetransformers, OpenAI embeddings, etc.). Python proficiency and experience with REST APIs, data processing libraries (pandas, NumPy), and JSON-LD. Preferred Qualifications Master's degree in Data Science, Computer Science, AI/ML, or a related field. Knowledge of cloud-native deployment is a plus (though not mandatory). Open-source contributions, blog posts, or internal project showcases in the GenAI/Knowledge Graph space.