AI/ML Engineer – Distributed Cloud

About the role

We are seeking a versatile and passionate AI professional to join our data science and engineering team. You will bridge the gap between research and production, building scalable machine‑learning systems that deliver business value.

Key responsibilities

• Design, develop, and deploy end‑to‑end AI pipelines, integrating Large Language Models (LLMs) and foundation models into production.
• Transition AI prototypes and experimental agents into scalable, production‑grade systems using modern LLM Ops practices.
• Write robust, efficient Python code with frameworks such as LangChain, LlamaIndex, AutoGPT, and traditional libraries like PyTorch or TensorFlow.
• Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking (e.g., RAGas or Arize Phoenix).
• Collaborate with Data Engineers to build efficient data pipelines for vector databases (Chroma, Pinecone, Weaviate) and optimise context retrieval for Retrieval‑Augmented Generation.
• Stay at the forefront of Generative AI, exploring new techniques in prompt engineering, fine‑tuning, and agentic workflows.

Required profile

• 3+ years of experience as an AI Engineer, ML Developer, or Software Engineer focused on AI integration.
• Strong proficiency in Python and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
• Practical experience with Generative AI, prompt engineering, and fine‑tuning foundation models (OpenAI, Hugging Face, Anthropic).
• Degree in Computer Science, Engineering, or a related quantitative field.
• Professional level of English (written and spoken).

Required skills

• Python
• LangChain
• LlamaIndex
• AutoGPT
• PyTorch
• TensorFlow
• RAGas
• Arize Phoenix
• Chroma, Pinecone, Weaviate (vector databases)
• SQL
• Azure AI, Vertex AI, AWS Bedrock
• Docker
• FastAPI / Flask