
Advanced AI Systems Architect
2 days ago
We are seeking a highly skilled and forward-thinking AI systems designer experienced in designing, deploying, and operationalizing modern AI solutions using Generative AI, Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) for intelligent multi-agent orchestration.
In this role, you'll build context-aware AI agents capable of dynamic memory management, tool-based reasoning, multi-modal interaction, and consistent state maintenance across distributed AI ecosystems. You'll work at the forefront of autonomous AI system design integrating multi-model workflows, RAG pipelines, tool-augmented agents, and persistent context protocols.
- Key Responsibilities:
- Design, develop, and deploy advanced AI systems leveraging LLMs, multi-modal models, and autonomous agent frameworks.
- Architect and implement Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases for dynamic, enterprise-safe context retrieval.
- Develop and manage context-aware AI agents leveraging Model Context Protocol (MCP) or equivalent structured context management mechanisms for persistent memory, multi-agent collaboration, and session continuity.
- Implement context propagation, state serialization, and contextual handoff mechanisms across distributed agents, tools, and reasoning chains.
- Integrate AI systems with cloud APIs, vector databases, plugin architectures, and orchestration frameworks for multi-step task execution.
- Optimize memory management, prompt engineering, and dynamic context windows for complex, long-running AI workflows.
- Lead AI agent orchestration initiatives using frameworks like LangChain, Semantic Kernel, CrewAI, or AutoGen, with MCP integration for context tracing and governance.
- Stay ahead of emerging trends in multi-agent LLM ecosystems, autonomous reasoning frameworks, and context-aware AI protocol standards like MCP.
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