Artificial Intelligence (AI), Business Case, Consulting, Credit Analysis, Credit Risk, Customer/Client Research, Employee Benefits, Information Technology & Information Systems, Injections, MCP - Microsoft Certified Professional, Metadata, Natural Language Processing (NLP), Onboarding, Ontology, Prototyping, Risk Analysis, Shallow Parsing, Short Messaging Service (SMS), Use Cases, Vector Based
Immediate need for a talented Agentic AI / Semantic Solutions Architect. This is a 06+months contract opportunity with long-term potential and is located in Atlanta, GA(Hybrid). Please review the job description below and contact me ASAP if you are interested.
Job ID: 26-17566
Pay Range: $80/hr - $95/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:
- Architect and design agentic AI workflows that consume outputs from semantic layers, including knowledge graphs, ontologies, and metadata catalogs
- Develop and prototype GraphRAG pipelines that combine graph traversal with vector-based retrieval for accurate, domain-grounded responses
- Define and implement context engineering strategies, including metadata injection, chunking, and semantic optimization for LLM prompts
- Design and build Model Context Protocol (MCP) server patterns to enable seamless interaction between agents and semantic data systems
- Develop LLM orchestration workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or AutoGen
- Build pipelines for automated metadata extraction and semantic tagging using NLP and LLM-based approaches
- Collaborate with Semantic Data Architects to ensure ontologies and graph structures are optimized for agent traversal and querying
- Prototype agent-based solutions for business use cases such as:
- Credit risk analysis
- Customer data onboarding workflows
Key Requirements and Technology Experience:
- Key skills; "Agentic" ,"RAG"," LLM", "Lang Chain"
- Strong expertise in Agentic AI architecture (multi-agent systems, tool usage, planning loops)
- Hands-on experience with GraphRAG design (hybrid graph + vector retrieval systems)
- Experience in LLM orchestration frameworks:
- LangChain, LangGraph, LlamaIndex, or AutoGen
- Deep understanding of context engineering techniques (chunking, windowing, semantic compression)
- Experience designing and integrating Model Context Protocol (MCP)
- Strong knowledge of semantic systems such as:
- Knowledge graphs
- Ontologies
- Metadata-driven architectures
Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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