AI Engineer

Cloud Employee, is a UK-owned business established 8 years ago. We connect high-performing software engineer talent worldwide with some of the world's leading and most innovative tech companies. Developers join to work as part of international engineering teams and grow their CV and skill set.

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We pride ourselves on being a supportive and cutting-edge workplace that continuously invests in staff development, engagement, and well-being. We provide security, and career paths, along with individual training programs and mentoring.

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• Remote work forever
• Competitive Salary
• Shift: Central timezone
• Position: Full-time

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• Design, develop, and deploy Large Language Model (LLM) applications using models like GPT-4, Claude, Llama, and Mistral
• Build agentic AI systems capable of complex reasoning, tool use, and autonomous decision-making
• Implement prompt engineering techniques to optimize LLM performance and reduce hallucinations
• Create efficient retrieval-augmented generation (RAG) systems for domain-specific applications
• Develop evaluation frameworks to benchmark LLM performance and fine-tune models
• Design and implement AI orchestration systems to manage multi-agent workflows
• Optimize AI inference processes for cost and performance balance
• Create APIs and interfaces for AI agent interaction with other systems
• Work with vector databases to enable semantic search capabilities
• Implement responsible AI practices with focus on safety, bias mitigation, and alignment

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• 3+ years of experience in AI/ML engineering, with at least 1 year working with modern LLMs
• Strong proficiency in Python and relevant AI/ML frameworks (PyTorch, TensorFlow, Hugging Face)
• Experience with LLM APIs and integration (OpenAI, Anthropic, etc.)
• Solid understanding of prompt engineering and context management techniques
• Experience with vector databases (e.g., Pinecone, Weaviate, Qdrant, Chroma)
• Proficiency with embedding models and semantic search implementation
• Knowledge of RAG architecture and implementation patterns
• Experience with containerization and deployment of AI applications (Docker, Kubernetes)

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• Experience with multi-agent systems and agent communication protocols
• Familiarity with LLMOps practices and tools
• Experience with FastAPI for building AI application backends
• Background in NLP and traditional machine learning methods
• Contributions to open-source LLM projects

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• Competitive Salary
• Benefits package includes training allowance, and 20 PTOs
• An annual salary increase, as laid out in the contract
• Remote work

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