We have partnered with a financial services client building a next-generation AI and ML infrastructure to power advanced analytics, automation, and customer intelligence across the business. The organisation is scaling its platform around Azure AI tools, MLOps pipelines, and large language model deployment, creating a cloud-first ecosystem designed for innovation and reliability.

About the role:

The DevOps Engineer will design, automate, and optimise the cloud infrastructure supporting AI and ML workloads. You'll work closely with data science and engineering teams to ensure seamless model deployment, scalability, and performance across environments. This includes implementing CI/CD pipelines, container orchestration, and end-to-end observability for production-grade AI systems.

About you:

• 5+ years of DevOps or Cloud Engineering experience, ideally within financial services
• Strong experience with Azure (including Azure Machine Learning, Azure AI Foundry, Cognitive Services, and related AI tools)
• Strong skills in Python, TensorFlow, PyTorch, and MLflow
• Hands-on experience with LLMs, vector databases (e.g. Pinecone, FAISS), and generative AI frameworks
• Deep understanding of MLOps, containerisation (Docker, Kubernetes), and cloud-based AI platforms (preferably Azure AI or OpenAI services via Azure)
• Strong problem-solving mindset and ability to work in fast-moving environments