Staff/ Principa/ MTS Agentic AI Architect – Knowledge Engineering
Core
Design and drive enterprise architecture for Agentic AI, Knowledge Engineering, and AI-powered decision systems across AWS, GCP, and on-prem environments to transform information into intelligence for engineering and manufacturing use cases.
Role type
Staff/Principal/MTS Agentic AI Architect (Knowledge Engineering)
Builds
Scalable multi-agent architectures, enterprise knowledge fabrics, ontologies, taxonomies, metadata models, knowledge graphs, and RAG/GraphRAG solutions.
Domain
Semiconductor/Storage industry + Agentic AI & Knowledge Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Agentic AI & A2A Systems, Knowledge Graphs & Semantic Systems, Generative AI & Retrieval, Hybrid Platform Architecture, AI Governance, Technology Leadership
Preferred skills
Industrial/Engineering Context, Claude Ecosystem, MCP & Tool Connectivity, GCP Architecture, On-Premises Engineering Systems
Technologies
AWS AgentCore, GCP, Neo4j, AWS Neptune, RDF/OWL, Pinecone, ChromaDB, Weaviate, Milvus, Qdrant, FAISS, Python, LangChain, LlamaIndex, LangGraph, JIRA, Confluence, SharePoint, Bitbucket
Responsibilities
Define enterprise architecture for Agentic AI and Knowledge Engineering; Design scalable multi-agent architectures using A2A collaboration and memory systems; Architect MCP-based access patterns for secure agent-tool interaction; Develop LLM Wiki architecture and knowledge curation workflows; Implement entity resolution and semantic interoperability across cloud and on-prem sources; Establish standards for security, compliance, and Responsible AI; Lead proof-of-concepts and mentor technical teams.
Seniority
Staff/Principal/MTS, hands-on IC with strategic leadership
