Overview:
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
Experience:
- 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.
- Expected Deliverables
- 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.
What do I need before I apply:
- To be flexible to travel to, and work at, client sites across the UK as require
Benefits:
- Collaborative working environment – we stand shoulder to shoulder with our clients and our peers through good times and challenges
- We empower all passionate technology loving professionals by allowing them to expand their skills and take part in inspiring projects
- Expleo Academy - enables you to acquire and develop the right skills by delivering a suite of accredited training courses
- Competitive company benefits
- Always working as one team, our people are not afraid to think big and challenge the status quo
#LI-DS1
- As a Disability Confident Committed Employer we have committed to:
- 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
“We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of their race, sex, disability, religion/belief, sexual orientation or age”.
We treat everyone fairly and equitably across the organisation, including providing any additional support and adjustments needed for everyone to thrive
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