Data Scientist ( GenAI & Knowledge Graphs )

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 Data Scientist GenAI & Knowledge Graphs in Seattle, WA. Below is the detailed job description.

Title: Data Scientist GenAI & Knowledge Graphs

Location: Seattle, WA, US

Department: AI & Data Science

Employment Type: Full-time

Job Description:

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 Prot g , 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 Prot g .

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.