Agentic AI Semantic Solutions Architect #19572

Job Title: Agentic AI / Semantic Solutions Architect

Location: Atlanta Georgia USA (Hybrid Onsite)

Job Summary

STAFFXPERT LLC is seeking an Agentic AI / Semantic Solutions Architect on behalf of our client in Atlanta Georgia USA.

In this role you will design and deliver advanced Agentic AI and semantic-driven architectures that leverage knowledge graphs ontologies metadata systems and LLM-based orchestration frameworks. You will be responsible for building GraphRAG pipelines multi-agent systems and context-aware AI solutions that enable intelligent domain-grounded decision-making across enterprise use cases such as credit risk analysis and customer onboarding.

Key Responsibilities

• Architect and design agentic AI systems using multi-agent workflows planning loops and tool-augmented LLM reasoning

• Develop and implement GraphRAG pipelines combining graph traversal and vector-based retrieval for accurate context-rich responses

• Design LLM orchestration workflows using frameworks such as LangChain LangGraph LlamaIndex or AutoGen

• Define and implement context engineering strategies including chunking windowing semantic compression and metadata injection

• Build and integrate Model Context Protocol (MCP) server architectures to enable seamless agent-to-data system interactions

• Develop pipelines for automated metadata extraction and semantic tagging using NLP and LLM-based techniques

• Collaborate with semantic data teams to optimize knowledge graphs and ontologies for AI-driven traversal and querying

• Prototype and deliver agent-based solutions for enterprise use cases including credit risk analysis and customer onboarding workflows

Required Qualifications

• 13 years of experience in software engineering AI/ML or data architecture roles

• Strong expertise in Agentic AI architectures including multi-agent systems tool usage and reasoning loops

• Hands-on experience with GraphRAG systems (hybrid graph vector retrieval architectures)

• Proficiency in LLM orchestration frameworks such as:

  • LangChain

  • LangGraph

  • LlamaIndex

  • AutoGen

• Strong understanding of context engineering techniques (chunking windowing semantic optimization prompt structuring)

• Experience designing or integrating Model Context Protocol (MCP) or similar agent-context communication systems

• Solid understanding of semantic data systems including knowledge graphs ontologies and metadata-driven architectures

Preferred Qualifications

• Experience with Google Vertex AI (Agent Builder / Search capabilities)

• Exposure to GCP Spanner Graph or similar graph database technologies

• Familiarity with metadata governance tools such as Collibra or Google Dataplex

• Experience with vector databases such as Pinecone Weaviate pgvector or Vertex AI Vector Search

• Prior experience in regulated industries such as financial services banking or legal systems