DevOps Engineer
AI Summary
Builds and operates cloud-native infrastructure for AI solutions, data pipelines, and platform services on Azure and AWS, automating CI/CD, monitoring, and deployment patterns to help AI teams move from prototype to production.
About this role
Overview
Expleo is a trusted partner for your innovation journey. As a global engineering, technology and consulting service provider, we are ideally positioned to help you achieve your ambitions and future-proof your business. With a smart blend of bold thinking and reliable execution, we’re able to fast-track innovation through each step of your value chain.
We are strategically positioned to build value, with global footprint across 30 countries.We are as global and local as you need us to be, with strong best-in-class pan-European technological centres and unique best-shoring capabilities.
We leverage a network of high value-adding affiliates in consulting and industrial excellence, and leading partners across multiple sectors to provide you with the most comprehensive services and solutions in an ever-changing environment.
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 by existing data or integration landscapes;
- 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 improving platform reliability, developer experience, cloud cost transparency, and operational maturity.
Essential skills
- 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, containerized 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 organizations;- Understanding of enterprise data engineering concepts such as ETL, data pipelines, data storage, and integration patterns – ideally with hands-on experience;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.
Desired skills
- 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 heterogenous multi-country enterprise environments;- Cloud certifications or hands-on experience with DevSecOps, platform engineering, or site reliability engineering practices.
Skills
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