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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud Engineer - **Company:** Expleo - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** .NET Framework, Artificial Intelligence, Application Services, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Data as a Services, DevOps, Github, Internet Hosting Service, Key Management, Network Security, Log Analysis, SQL Azure, Role-Based Access Control, OpenAI, Azure Active Directory, Cloud Services, Runbook, Search Technologies, Software Deployment, Systems Integration, Enterprise Search, Azure Service Bus, Data Logging, Software Repository, Cloud Monitoring, Retrieval-Augmented Generation, Generative AI, Indexer, Git, Build Management, Containerization, Git Flow, Infrastructure Automation Frameworks, Deployment Automation, Azure AKS, Terraform, Serverless Computing, Docker, Container Apps - **Published:** October 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c4512f99573630df ## About the Role * Azure Platform Engineering + Strong hands-on experience designing, building and deploying cloud-native solutions in Microsoft Azure. + Practical experience with Azure AI Search, including service deployment, indexing and integration with application or data services. + Experience deploying and managing Azure SQL serverless capabilities and Azure Service Bus. + Experience deploying .NET applications using Azure container services, such as Azure Container Apps, or an equivalent Azure hosting service. + Experience with Azure Storage Accounts, Azure Key Vault, Azure Monitor and Log Analytics. + Good understanding of Azure networking, including virtual networks, private endpoints and network security controls. + Experience implementing identity and access controls using Microsoft Entra ID, role-based access control and managed identities. + Infrastructure as Code + Proven experience using Terraform to provision and manage Azure infrastructure. + Experience developing reusable Terraform modules, remote state patterns and repeatable environment deployments. + Ability to structure Infrastructure-as-Code repositories and apply appropriate validation, review and release controls. * DevOps and CI/CD + Experience creating CI/CD pipelines using Azure DevOps or GitHub Actions. + Experience automating infrastructure and application deployments across multiple environments. + Confident use of Git, branching strategies, pull requests and code review practices. + Containerisation + Experience packaging, deploying and supporting containerised .NET applications. + Hands-on knowledge of Docker and Azure container hosting services. + Understanding of container configuration, secrets, networking, logging, health checks and scaling. * Desirable Experience + Experience delivering AI, generative AI, enterprise search or Retrieval-Augmented Generation solutions. + Exposure to Azure OpenAI, vector search, semantic search or document indexing patterns. + Experience integrating Azure AI Search with structured and unstructured data sources. + Knowledge of Azure Kubernetes Service where it forms part of the wider platform. + Experience working in enterprise-scale or regulated environments with established security, governance and compliance controls. + Knowledge of cost management, resilience, backup and disaster recovery considerations for Azure workloads. ## Description We are looking for an experienced Cloud Engineer specialising in Microsoft Azure to join the team on a short-term engagement. The role will support the hands-on build and deployment of cloud capabilities required for an initial Azure AI Search use case and the wider platform foundations around it. This is a delivery-focused position. The successful candidate will translate solution requirements into secure, scalable and repeatable Azure infrastructure, with particular ownership of the physical build, configuration, automation and Terraform-based deployment pipeline. You will work closely with architects, AI specialists, application developers and platform teams to establish production-ready cloud services and leave clear documentation and handover materials. The ideal candidate is a practical, delivery-oriented Azure engineer who can become productive quickly and work with a high degree of autonomy. You will be comfortable moving from architecture and requirements into a working implementation, while maintaining a strong focus on security, automation, repeatability, supportability and clear documentation. Responsibilities: * Design, build, configure and deploy Azure cloud infrastructure supporting AI-enabled search and associated application services. * Implement and manage Azure AI Search, Azure SQL serverless capabilities, Azure Service Bus and containerised .NET workloads. * Create and maintain Infrastructure as Code using Terraform, including reusable modules and environment-specific configuration. * Build and configure CI/CD pipelines for automated infrastructure and application deployment. * Configure Azure networking, identity, access controls, secrets management, monitoring and logging in line with cloud engineering best practice. * Support the establishment of development, test and production environments, including repeatable deployment patterns. * Collaborate with solution architects, software engineers, AI specialists and security stakeholders to integrate services into the wider architecture. * Troubleshoot deployment and integration issues, improving reliability, performance, security and cost efficiency. * Produce clear technical documentation, deployment guides, operational runbooks and support materials. * Provide structured knowledge transfer and handover at the end of the assignment. Essential skills: * Microsoft Azure * Terraform * Azure AI Search * Azure SQL serverless capabilities * Azure Service Bus * CI/CD pipelines * Git * Docker and containers * Azure DevOps or GitHub Actions * Azure OpenAI * Azure Kubernetes Service * C# / .NET engineering knowledge, + Azure AI Search infrastructure built, configured and integrated for the initial use case. + Azure SQL serverless capabilities and associated data services deployed and configured. + Azure Service Bus messaging capability implemented where required by the solution. + Containerised .NET workloads deployed using the agreed Azure hosting service. + Terraform modules, environment configuration and state management established. + Automated deployment pipelines created and tested. + Monitoring, logging, security and operational controls configured. + Technical documentation, runbooks and deployment guidance completed. + Knowledge transfer and final handover delivered to the internal team. * Success Measures + Cloud services can be deployed consistently through the agreed Terraform and pipeline process. + The initial AI Search use case has the required Azure platform capabilities available and operational. + Infrastructure is appropriately secured, monitored and documented. + The internal team can support, maintain and extend the delivered solution following handover., + Ensure our recruitment process is inclusive and accessible + Communicating and promoting vacancies + Offering an interview to disabled people who meet the minimum criteria for the job + Anticipating and providing reasonable adjustments as required + Supporting any existing employee who acquires a disability or long term health condition, enabling them to stay in work at least one activity that will make a difference for disabled people