Advanced AI Professional

2 days ago

Alleppey, Kerala, India beBeeAI Full time US$ 2,20,000 - US$ 2,60,000
Artificial Intelligence Engineer

Job Overview:

We are seeking a highly skilled and forward-thinking AI professional experienced in designing, deploying, and operationalizing modern AI solutions using Generative AI frameworks, Agentic AI orchestration frameworks, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) for intelligent multi-agent orchestration.

  • Design, Develop, and Deploy Advanced AI Systems: Leverage LLMs, multi-modal models, and autonomous agent frameworks to build context-aware AI agents capable of dynamic memory management, tool-based reasoning, multi-modal interaction, and consistent state maintenance across distributed AI ecosystems.
  • Architect and Implement RAG Pipelines: Integrate with vector databases for dynamic, enterprise-safe context retrieval, and ensure persistence and session continuity.
  • Develop and Manage Context-Aware AI Agents: Utilize MCP or equivalent structured context management mechanisms for persistent memory, multi-agent collaboration, and session continuity.
  • Implement Context Propagation and State Serialization: Enable seamless communication and data exchange across distributed agents, tools, and reasoning chains.

About the Role:

  • Optimize memory management, prompt engineering, and dynamic context windows for complex, long-running AI workflows.
  • Integrate AI systems with cloud APIs, vector databases, plugin architectures, and orchestration frameworks for multi-step task execution.
  • 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.

Requirements:

  • 3+ years of experience in AI engineering, with direct expertise in: Generative AI (GenAI) frameworks, Agentic AI orchestration frameworks, Retrieval-Augmented Generation (RAG) system design, and Model Context Protocol (MCP).
  • Strong software engineering skills in Python, including AI/ML libraries like PyTorch, TensorFlow, Transformers, and RAG toolkits.
  • Hands-on experience working with vector databases (Pinecone, FAISS, Weaviate, Chroma) and plugin-based AI architectures.
  • Strong understanding of AI memory management, session context propagation, and multi-agent communication protocols.
  • Programming framework/language: Python, JS, or Java.
  • Experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Solid understanding of statistics, data structures, and algorithms.

Preferred Skills:

  • Experience integrating multi-modal models (text, image, audio, video) into agentic workflows.
  • Familiarity with AI safety, observability, and context integrity management in distributed AI systems.
  • Exposure to LLMOps pipelines, prompt optimization techniques, and AI agent performance tuning.
  • Experience contributing to open-source AI orchestration frameworks or context management libraries.
  • Understanding of AI alignment, ethical AI principles, and responsible AI design.
  • Experience with Deep learning in NLP, computer vision, or reinforcement learning.
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