AI Systems Architect

1 day ago

Alwar, Rajasthan, India beBeeArtificial Full time ₹ 2,00,00,000 - ₹ 2,20,00,000
Job Opportunity

We are seeking a highly skilled and forward-thinking AI Engineer to join our team. The ideal candidate will have experience 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.

Key responsibilities include:

  • Designing and developing advanced AI systems leveraging Large Language Models (LLMs), multi-modal models, and autonomous agent frameworks.
  • Architecting and implementing Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases for dynamic, enterprise-safe context retrieval.
  • Developing and managing context-aware AI agents leveraging Model Context Protocol (MCP) or equivalent structured context management mechanisms for persistent memory, multi-agent collaboration, and session continuity.
  • Implementing context propagation, state serialization, and contextual handoff mechanisms across distributed agents, tools, and reasoning chains.
  • Integrating AI systems with cloud APIs, vector databases, plugin architectures, and orchestration frameworks for multi-step task execution.

Required Experience:

The ideal candidate will have 3+ years of AI engineering experience, with direct expertise in:

  • Generative AI (GenAI) frameworks such as OpenAI, Hugging Face, Anthropic, and Mistral.
  • Agentic AI orchestration frameworks including LangChain, Semantic Kernel, AutoGen, and 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 such as PyTorch, TensorFlow, Transformers, and RAG toolkits.
  • Hands-on experience working with vector databases and plugin-based AI architectures.

Preferred Skills:

The ideal candidate will also have exposure to:

  • Multi-modal models integration into agentic workflows.
  • AI safety, observability, and context integrity management in distributed AI systems.
  • LLMOps pipelines, prompt optimization techniques, and AI agent performance tuning.
  • Contributing to open-source AI orchestration frameworks or context management libraries.

Education Qualification:

A Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field is required.

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