Senior AI Engineer

15 hours ago

Udaipur, Rajasthan, India beBeeArtificialIntelligenceEngineer Full time ₹ 40,00,000 - ₹ 50,00,000
AI Systems Architect

We are seeking a highly skilled and forward-thinking AI engineer 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.

  • Design, develop, and deploy advanced AI systems leveraging Large Language Models (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.
Requirements
  • 3+ years of AI engineering experience, with direct expertise in:
  • Generative AI (GenAI) frameworks (OpenAI, Hugging Face, Anthropic, Mistral)
  • Agentic AI orchestration frameworks (LangChain, Semantic Kernel, AutoGen, CrewAI)
  • Retrieval-Augmented Generation (RAG) system design and deployment
  • Model Context Protocol (MCP) or structured context management solutions in multi-agent, multi-tool AI workflows
  • 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.
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.
Education Qualification
  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.

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