Generative AI & Knowledge Graph Engineer

  • Seattle, WA
  • Posted 5 days ago | Updated 1 hour ago

Overview

On Site
$DOE
Full Time

Skills

Generative AI

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 (Title) in (Location). Below is the detailed job description.

Job Title: Generative AI & Knowledge Graph Engineer

Location: Seattle, WA (Onsite)
Job Type: Full-Time
Job Description

We are seeking an experienced Generative AI & Knowledge Graph Engineer to join our advanced AI engineering team in Seattle, WA. This role is fully onsite and full-time. The ideal candidate will have hands-on expertise in building, deploying, and scaling Generative AI solutions along with deep experience in Knowledge Graphs, semantic technologies, and enterprise-grade data systems.

Key Responsibilities

  • Design, develop, and deploy Generative AI models (LLMs, Agentic systems, RAG pipelines).

  • Build and maintain Knowledge Graphs using semantic modeling, ontologies, and graph databases.

  • Integrate LLMs with Knowledge Graphs to enable reasoning, retrieval, and intelligent automation.

  • Develop scalable RAG pipelines using vector databases, embeddings, and entity linking.

  • Implement KG-based reasoning, relationship extraction, and semantic search.

  • Collaborate with data engineering and product teams to deliver AI-driven solutions.

  • Optimize model performance, latency, and cost for production environments.

  • Ensure data quality, governance, and schema integrity across KG systems.

  • Stay current with GenAI, LLM, and graph technology advancements.

Required Skills & Experience

  • 5 10+ years of experience in AI/ML, NLP, or Data Engineering.

  • Strong experience with Generative AI / LLMs (OpenAI, Llama, Gemini, custom finetuning).

  • Hands-on experience with Knowledge Graphs, ontologies, graph modeling, RDF, OWL, SPARQL.

  • Expertise with Graph Databases: Neo4j, AWS Neptune, TigerGraph, or similar.

  • Strong Python development skills; experience with ML frameworks (PyTorch, TensorFlow).

  • Experience building RAG, embedding pipelines, and vector DBs (FAISS, Chroma, Pinecone).

  • Understanding of NLP, entity extraction, embeddings, relation extraction.

  • Experience with cloud platforms (AWS/Azure/Google Cloud Platform), preferably AWS.

  • Strong problem-solving and architectural design skills.

Preferred Qualifications

  • Experience with Knowledge Graph + LLM hybrid architectures.

  • Experience developing agentic AI workflows or LLM-based agents.

  • Knowledge of MLOps concepts: model monitoring, CI/CD, automation pipelines.

  • Master's or PhD in Computer Science, AI, Data Science, or related field.

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