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Llm Knowledge Graph Jobs in Georgia (NOW HIRING)

Northern Base

AI and Fabric Engineer

Atlanta, GA · On-site

$110K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

LLM / GenAI: Azure OpenAI/OpenAI, RAG, embeddings, vector search, hybrid search, * prompt ... knowledge graphs, RDF/OWL/SPARQL or graph databases. * Engineering: Python, SQL, Spark/PySpark ...

2T Consulting

Expertise in LLM/GenAI solutions including Azure OpenAI/OpenAI, RAG, embeddings, vector search ... lineage, semantic layers, knowledge graphs, RDF/OWL/SPARQL, or graph databases. * Strong ...

New

2T Consulting

Expertise in LLM/GenAI solutions including Azure OpenAI/OpenAI, RAG, embeddings, vector search ... lineage, semantic layers, knowledge graphs, RDF/OWL/SPARQL, or graph databases. * Strong ...

New

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Llm Knowledge Graph information

What is the difference between Llm Knowledge Graph vs Data Scientist?

AspectLlm Knowledge GraphData Scientist
Required CredentialsKnowledge of NLP, graph databases, machine learningStatistics, programming, data analysis
Work EnvironmentResearch labs, AI companies, tech firmsCorporate, consulting, research institutions
Industry UsageAI, knowledge management, semantic webBusiness analytics, predictive modeling

While both roles involve data and machine learning, Llm Knowledge Graph specialists focus on building interconnected knowledge bases using NLP and graph technologies, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap in AI projects but serve different core functions within organizations.

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Llm Knowledge Graph jobs near you

Context & Memory Engineer - Q126

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Re-posted 11 days ago

Job description

Overview:
Job Title: Context & Memory Engineer
Company: R2 Technologies
Location: Alpharetta, GA (Hybrid / Remote Options Available)
Employment Type: Full-Time / Contractual
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we have built a reputation as a trusted partner for IT staffing excellence and cutting-edge digital product innovation. We are driven by innovation and operate on a simple philosophy: "We deliver what we promise, and we promise only what we can deliver." Beyond providing top-tier IT talent, R2 builds cutting-edge proprietary solutions like SmartEnt-an Enterprise AI & IoT Intelligence Platform utilizing advanced NLP and AI technologies. By partnering closely with our clients, we deliver technology-driven outcomes that are realistic, measurable, and impactful.
Job Summary: An AI's output is only as good as the context it is grounded in. R2 Technologies is looking for a Context & Memory Engineer to build the connective tissue between our enterprise data and advanced language models. You will be responsible for ensuring our autonomous systems maintain persistent state, conversational continuity, and semantic understanding without compromising data security or speed.
Key Responsibilities: * Architect and maintain advanced Retrieval-Augmented Generation (RAG) pipelines that feed highly relevant, real-time enterprise context to foundation models.
  • Implement and manage stateful memory architectures for LLM agents using the Model Context Protocol (MCP) and long-term storage mechanisms.
  • Deploy, optimize, and tune Vector Databases (e.g., Pinecone, Qdrant, Milvus) and Graph Databases (e.g., Neo4j) to map complex semantic relationships and entity graphs.
  • Develop chunking, embedding, and re-ranking strategies to maximize the accuracy and relevance of context retrieved for the AI models.
  • Monitor token limits and optimize context window utilization to balance latency, cost, and reasoning quality.
  • Actively utilize AI-assisted development tools to accelerate the construction of data ingestion and semantic mapping pipelines.

Qualifications: * Up to 3 years of experience in Data Engineering, AI/ML Engineering, or Backend Development.
  • Strong proficiency in Python and familiarity with data orchestration pipelines.
  • Hands-on experience building RAG systems and working with frameworks like LlamaIndex or LangChain.
  • Experience deploying and querying Vector Databases and/or Knowledge Graphs.
  • Proven experience or strong familiarity working alongside AI coding assistants to enhance productivity.
  • Understanding of embedding models, semantic search techniques, and the nuances of LLM context windows (e.g., Claude's 200k+ context capabilities).

Skills:
mcp,rag

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