Vacancy Description
Responsibilities
- Build customer-facing AI applications powered by leading LLMs such as Claude, GPT, Llama, Mistral, and other foundation models
- Architect and optimize advanced RAG, Hybrid RAG, Agentic RAG, and Graph RAG solutions
- Develop and maintain scalable data pipelines supporting AI applications and knowledge systems
- Design and implement multi-agent workflows using frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel
- Develop and integrate Model Context Protocol (MCP) servers, tools, and enterprise connectors
- Evaluate AI model performance using observability and evaluation frameworks, improving accuracy, grounding, relevance, and response quality
- Implement prompt engineering strategies, tool calling, structured outputs, workflow orchestration, and AI memory management
- Deploy AI solutions in cloud and enterprise environments using modern DevOps and LLMOps practices
- Collabora...
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