Our client is an organization focused on using artificial intelligence to automate complex knowledge-based workflows and improve operational efficiency. They are building an internal multi-agent AI ecosystem designed to support research, content, business development, and other business processes while maintaining strong standards for security, governance, auditability, and human oversight.

Role Overview
As the AI Engineer, you will be responsible for designing, building, deploying, and operating an internal multi-agent AI system that automates complex knowledge-based workflows.

You will own the AI system end-to-end, from architecture and development through deployment, integration, monitoring, and continuous improvement. Working directly with leadership, you will translate business requirements into reliable AI solutions while ensuring appropriate governance, security, auditability, and human oversight.




This is a build-and-own role for an engineer with experience taking AI applications into production who is comfortable owning complete systems rather than working only on isolated technical tasks.

Location
Fully remote | 9:00 AM - 5:00 PM EST
Key Responsibilities
AI Agent Development & System Architecture
Design, build, and maintain production-ready multi-agent AI systems.
Develop AI solutions that automate research, content, and business development workflows.
Architect scalable agent workflows with appropriate human oversight and governance.
Define engineering standards and best practices for AI system development.
Own the long-term operation, maintenance, and continuous improvement of AI systems.

Retrieval-Augmented Generation (RAG) & Knowledge Systems
Build and maintain Retrieval-Augmented Generation (RAG) systems using vector databases.
Develop knowledge retrieval workflows using embeddings, semantic search, and retrieval optimization.
Evaluate retrieval quality and continuously improve knowledge system performance.
Create governed AI knowledge systems desi

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