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Llm Knowledge Graph Jobs in Georgia (NOW HIRING)

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

AI & Microsoft Fabric Engineer

Rex, GA · On-site

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 ...

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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

AI & Microsoft Fabric Engineer

2T Consulting

Mableton, GA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

We are seeking an AI & Microsoft Fabric Engineer to design and develop enterprise AI solutions using Agentic AI, Generative AI, Azure OpenAI, RAG, and Microsoft Fabric. The role focuses on building AI agents, semantic data solutions, and scalable data pipelines to automate workflows and enable intelligent data-driven decisions.

Required Skills
  • Strong experience with Agentic AI, including AI agents, reasoning, planning, memory, tool/function calling, multi-agent orchestration, guardrails, and evaluation.
  • Hands-on experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar AI orchestration frameworks.
  • Expertise in LLM/GenAI solutions including Azure OpenAI/OpenAI, RAG, embeddings, vector search, hybrid search, prompt engineering, grounding, and hallucination mitigation.
  • Strong Microsoft Fabric experience with:
    • Lakehouse, Warehouse, OneLake
    • Data Factory, Dataflows, Notebooks
    • Power BI semantic models, Direct Lake, Delta Lake
    • Medallion architecture
  • Experience with ontology and semantic modeling, including entities, relationships, taxonomy, metadata, lineage, semantic layers, knowledge graphs, RDF/OWL/SPARQL, or graph databases.
  • Strong programming skills in Python, SQL, Spark/PySpark, REST APIs, Git, CI/CD, monitoring, logging, and cloud security.
Roles & Responsibilities
  • Design and implement enterprise-grade Agentic AI solutions using LLMs, RAG, APIs, and enterprise data sources.
  • Integrate AI agents with Microsoft Fabric Lakehouse/Warehouse, semantic models, applications, and document repositories.
  • Build and optimize RAG pipelines using embeddings, vector/semantic search, structured data grounding, and evaluation frameworks.
  • Develop ontology-driven semantic models supporting business rules, metadata, governance, and data lineage.
  • Design and build Fabric data solutions using Data Factory, Notebooks, Spark/PySpark, SQL, Delta Lake, and medallion architecture.
  • Implement AI governance practices including guardrails, access controls, monitoring, logging, security, and cost optimization.
  • Create technical designs, architecture diagrams, reusable components, and development standards.
  • Collaborate with business and technical teams to translate business processes into semantic data products and AI workflows.
Preferred Qualifications
  • Experience delivering production-grade GenAI and AI automation solutions.
  • Strong Azure cloud experience and enterprise data platform knowledge.
  • Experience with Agile development and production support.

Apply