AI Platform Engineer: RAG & Multi-Agent Orchestration

Artifintech; Atlanta (GA); On-site; USD 74,000 - 105,000; Full time

Job summary

Artifintech is seeking an AI Engineer in Atlanta to design and implement multi‑agent orchestration frameworks and agentic workflows. The role focuses on building Retrieval-Augmented Generation solutions that leverage structured and unstructured enterprise data across SharePoint, databases, and external sources.

Responsibilities include productionizing LLM-based applications with observability, performance optimization, and security controls; architecting scalable AI platform capabilities; and

Qualifications

• Experience designing multi-agent orchestration frameworks and agentic workflows.
• Proficiency with Retrieval-Augmented Generation (RAG) using structured and unstructured data.
• Develop and integrate enterprise knowledge retrieval across SharePoint, databases, and external sources.
• Implement AI governance: explainability, auditability, source traceability, human review workflows.

Responsibilities

• Design and implement multi-agent orchestration and agentic workflows.
• Build RAG solutions leveraging enterprise data sources.
• Develop knowledge retrieval platforms across repositories and external sources.
• Implement AI governance, traceability, and review workflows.
• Productionize LLM-based applications with observability and security controls.
• Lead technical design discussions and mentor teams on AI engineering best practices.

Skills

Multi-Agent Systems

Agent Orchestration Frameworks

Semantic Search

Knowledge Graphs

Tools

Git

GitHub

Bitbucket

FastAPI

Flask

Postgres pgvector

Pinecone

Elasticsearch

FAISS

REST APIs

LangChain

LangGraph

Azure OpenAI

OpenAI APIs

Job description

Artifintech is seeking an AI Engineer in Atlanta to design and implement multi‑agent orchestration frameworks and agentic workflows. The role focuses on building Retrieval-Augmented Generation solutions that leverage structured and unstructured enterprise data across SharePoint, databases, and external sources.

Responsibilities include productionizing LLM-based applications with observability, performance optimization, and security controls; architecting scalable AI platform capabilities; and