This is a remote position.
Design and implement a scalable data architecture integrating with the Eliza framework
Develop advanced vector embedding systems for semantic knowledge representation
Create multimodal memory structures supporting both episodic and semantic agent memory
Implement efficient RAG (RetrievalAugmented Generation) pipelines with vector database integration
Design context window optimization systems to maximize relevant information retrieval
Build knowledge graph structures for entity relationship tracking across project artifacts
Develop APIs for bidirectional enterprise tool integration JIRA Project Server etc.
Implement secure data partitioning to maintain compliance with financial industry standards
Create crossagent knowledge sharing protocols adhering to specified access controls
Design and implement observability systems for agent memory and knowledge retrieval
Requirements
Indepth experience with the Eliza framework and its agent coordination capabilities
Practical implementation experience with vector databases Pinecone Weaviate Milvus or Chroma
Handson experience with embedding models (e.g. OpenAI Cohere or opensource alternatives)
Deep knowledge of LangChain/LlamaIndex for agent memory and tool integration
Experience designing and implementing knowledge graphs at scale
Strong background in semantic search optimization and efficient RAG architectures
Experience with Model Control Plane (MCP) for both LLM orchestration and enterprise system integration
Advanced Python development with expertise in async patterns and API design
Benefits
Full Time Employment with competitive salary and benefits
Medical dental and vision insurance coverage
Eliza framework, Pinecone, Weaviate, Milvus, Chroma, OpenAI, Cohere, LangChain/LlamaIndex, Model Control Plane (MCP)
Education
Bachelor's Degree