Semantic Solutions Architect

Job Title : Agentic AI / Semantic Solutions Architect
Location : Atlanta, Georgia, USA (Hybrid)
Duration : 12 Months
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

Mandatory Skills

• 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