DevOps Engineer

We are looking for a DevOps Engineer for a fully remote position.

About the Role

You will build and operate the cloud foundation for a central AI team and AI Hubs, making AI use cases, agents, data products and platform components reliable, scalable, secure and ready for production across multiple countries. You work hands-on with AI products, engineering, data and platform teams to design and automate cloud-native infrastructure with a strong focus on Azure, while also supporting selected AWS-based data and integration workloads where relevant.

You are a pragmatic cloud engineer who enjoys turning ambitious AI ideas into stable, automated, production-ready services. You are comfortable working across cloud platforms, engineering teams and country IT organisations, and you know how to balance speed, reliability, security and cost.

Main Responsibilities

• Build and operate cloud-native infrastructure for AI solutions, data pipelines, APIs, agents and platform services, with Azure as the primary platform and AWS used where required.
  
• Create reusable infrastructure, deployment, observability and environment patterns that help AI teams move from prototype to production faster.
  
• Automate provisioning, configuration, CI/CD, monitoring, logging, secrets management and cost controls for AI workloads.
  
• Support cloud architecture decisions for agentic workflows, model integrations, event-driven services, data platforms and external APIs.
  
• Work with security and data protection teams to ensure cloud environments follow group standards for identity, access, encryption, logging, isolation and operational resilience.
  
• Collaborate with country IT and local teams to onboard environments, connect systems, troubleshoot deployments and scale successful AI use cases.
  
• Continuously improve platform reliability, developer experience, cloud cost transparency and operational maturity.
  

Requirements

Mandatory

• Experience with cloud-native development and deployment, ideally with strong Azure experience and practical exposure to AWS.
  
• Strong hands-on experience with infrastructure automation (IaC), CI/CD, containerised workloads, monitoring, logging and operational support.
  
• Solid engineering skills in Python, SQL and optionally TypeScript, with the ability to support APIs, data workflows and platform integrations.
  
• Experience working in cross-functional, international teams and with local IT organisations.
  
• Understanding of enterprise data engineering concepts such as ETL, data pipelines, data storage and integration patterns.
  
• Comfortable using GenAI software engineering tools such as GitHub Copilot, Cursor or OpenCode to accelerate delivery.
  
• Pragmatic, outcome-driven and comfortable operating in an evolving AI environment.
  
• Fluent English.
  

Nice to Have

• Experience with Snowflake, Azure AI Foundry, Microsoft Agent Framework, LangChain, MCP or comparable AI platform tooling.
  
• Exposure to frontend development, developer portals, workflow builders or internal platform user interfaces.
  
• Experience in heterogeneous multi-country enterprise environments.
  
• Cloud certifications or hands-on experience with DevSecOps, platform engineering or site reliability engineering practices.