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AI Engineer Manager

๐Ÿ•’ 28 days ago
AI SystemsML SystemsRAG SystemsLLM-powered Solutions

๐Ÿ“œ Description

  • Leading AI project delivery end to end, ensuring clear governance, strong stakeholder communication, and reliable execution.
  • Designing and building robust RAG systems, agentic frameworks, and LLM-powered solutions suitable for production environments.
  • Applying advanced prompt engineering techniques, including instruction design, few-shot prompting, structured outputs, and tool/agent prompts.
  • Running structured experiments across prompts, retrievers, chunking strategies, embeddings, reranking approaches, and models.
  • Building scalable inference infrastructure and CI/CD pipelines for AI and ML models.
  • Mentoring junior engineers and contributing to proposals, solution design, and new business initiatives.

๐Ÿ› ๏ธ Requirements

  • 6+ years of experience building and deploying AI, ML, or data-driven solutions in production environments.
  • Strong expertise in Python and solid Git practices.
  • Hands-on experience with LLM-powered solutions, RAG systems, and modern GenAI development patterns.
  • Practical experience with RAG components, including chunking, embeddings, retrieval, reranking, and evaluation.
  • Strong understanding of prompt engineering techniques, including structured outputs, few-shot prompting, instruction design, and tool/agent prompts.
  • Experience with MLOps/LLMOps practices and tools such as MLflow, Weights & Biases, or similar platforms.

โœจ Benefits

  • โš–๏ธ Flexible working options to help you strike the right balance.
  • ๐Ÿ‘จ๐Ÿฝโ€๐Ÿ’ป All the equipment you need to harness your talent (Macbook and accessories).
  • ๐Ÿ“š Learning opportunities:
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