What are the responsibilities and job description for the Agentic AI / Semantic Solutions Architect position at TekDallas?
Job Title: Agentic AI / Semantic Solutions Architect
Location: Atlanta, GA (Hybrid)
Duration: Long Term Contract
Job Summary
We are seeking an experienced Agentic AI / Semantic Solutions Architect to design and develop AI-powered solutions leveraging Large Language Models (LLMs), Knowledge Graphs, Semantic Technologies, and GraphRAG architectures. The ideal candidate will have strong experience building AI agents, semantic search solutions, metadata-driven systems, and enterprise AI applications using modern AI frameworks and cloud technologies.
Responsibilities
- Design and implement Agentic AI and multi-agent architectures for enterprise applications.
- Develop GraphRAG solutions combining vector search and knowledge graph retrieval.
- Build AI workflows using LangChain, LangGraph, LlamaIndex, AutoGen, or similar frameworks.
- Design semantic data models, ontologies, metadata frameworks, and knowledge graphs.
- Develop prompt engineering and context management strategies for LLM applications.
- Integrate AI solutions with enterprise data platforms and APIs.
- Build and optimize vector search and semantic retrieval systems.
- Collaborate with business and technical teams to deliver AI-driven solutions.
- Create proof-of-concepts and scalable AI architectures.
- Ensure AI solutions follow security, governance, and best practices.
Required Skills
- 10 years of overall IT experience.
- Strong experience with Agentic AI, Generative AI, and Large Language Models (LLMs).
- Hands-on experience with LangChain, LangGraph, LlamaIndex, AutoGen, or similar AI frameworks.
- Experience with Retrieval-Augmented Generation (RAG) and GraphRAG architectures.
- Strong understanding of Knowledge Graphs, Ontologies, Semantic Modeling, and Metadata Management.
- Experience with Prompt Engineering and Context Engineering.
- Knowledge of Model Context Protocol (MCP).
- Experience with Vector Databases such as Pinecone, Weaviate, ChromaDB, pgvector, or Vertex AI Vector Search.
- Programming experience in Python.
- Experience with REST APIs, microservices, and cloud platforms.
- Strong understanding of NLP, Machine Learning, and AI solution architecture.
- Experience with Git, CI/CD, and Agile methodologies.
Preferred Skills
- Experience with Google Cloud Platform (Google Cloud Platform) and Vertex AI.
- Knowledge of Spanner Graph, Dataplex, or Collibra.
- Experience with Neo4j, RDF, SPARQL, Graph Databases, and Semantic Web technologies.
- Experience in Financial Services, Banking, Insurance, or regulated industries.
- Knowledge of AI governance, security, and compliance frameworks.