naukri
Agentic AI Architect
Client of AIQU
KSA
Senior
Onsite
Discovered 4 weeks ago
Agentic AI ArchitectureMulti-Agent OrchestrationGraph RAGMCP (Model Context Protocol)Prompt EngineeringEngineering Tool Invocation
Free
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Agentic AI ArchitectureMulti-Agent OrchestrationGraph RAG
Role Overview
The objective of this project is to develop and deploy a sophisticated AI ecosystem leveraging Expert Digital Engineer's capabilities to transition from traditional RAG (Retrieval-Augmented Generation) to an Agentic AI Framework.
This system will integrate deep engineering knowledge, automate complex technical workflows, and provide decision support for Master Plans, Project Studies, and Operational Troubleshooting.
Key Skills for This Role
Agentic AI ArchitectureMulti-Agent OrchestrationGraph RAGMCP (Model Context Protocol)Prompt EngineeringEngineering Tool Invocation
Full Job Posting
Agentic AI Architect
The objective of this project is to develop and deploy a sophisticated AI ecosystem leveraging Expert Digital Engineer's capabilities to transition from traditional RAG (Retrieval-Augmented Generation) to an Agentic AI Framework.
This system will integrate deep engineering knowledge, automate complex technical workflows, and provide decision support for Master Plans, Project Studies, and Operational Troubleshooting.
Technical Scope & Core Capabilities
- Develop and deploy a sophisticated AI ecosystem leveraging Expert Digital Engineer's capabilities.
- Integrate deep engineering knowledge, automate complex technical workflows, and provide decision support for Master Plans, Project Studies, and Operational Troubleshooting.
- Implement a multi-agent system using LangGraph to manage complex, non-linear workflows where specialized agents collaborate to solve technical problems.
- Transition from vector-only search to Graph RAG, utilizing Knowledge Graphs to maintain relationships between complex engineering entities.
- Implement MCP (Model Context Protocol) to standardize how AI agents interact with external data sources and tools.
- Develop and optimize prompt templates to ensure high-precision outputs for technical engineering queries.
- Enable AI agents to programmatically trigger and interface with specialized industry software, including Hysys, OLGA, and Ansys.
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