We are seeking an experienced Senior Azure Cloud Engineer to design, build, automate, and operate secure, scalable, and cost-efficient cloud solutions on Microsoft Azure.
In this role, you will work hands-on with Azure infrastructure, containers, DevOps pipelines, Infrastructure as Code, observability, security controls, and AI-enabled cloud solutions. You will help translate architecture standards into working platforms, reusable deployment patterns, automation, and production-ready services.
You will collaborate closely with Cloud Architects, Platform Engineering, DevOps, Security, Networking, Data, AI, and Product teams to deliver robust Azure solutions that support modern application delivery, containerized workloads, and AI-enabled enterprise capabilities.
We would like to inform you that this role is primarily offered under a standard employment contract, in accordance with applicable labor regulations.
Feel free to work remotely from anywhere across Latvia or connect with colleagues at our Riga office.
- Design, implement, and maintain Azure cloud infrastructure, including subscriptions, resource groups, networking, identity, governance, security, and platform services
- Build and support reusable Azure deployment patterns for applications, APIs, front-end workloads, microservices, containers, serverless services, data integrations, and AI-enabled solutions
- Implement and operate Azure Kubernetes Service environments, including node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry integration, and security controls
- Build, maintain, and improve Infrastructure as Code using Terraform, including reusable modules, multi-environment deployments, automated validation, and integration with CI/CD pipelines
- Design and implement CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar tools
- Support DevOps practices such as automated builds, testing, security scanning, artifact management, environment promotion, deployment approvals, rollback strategies, and release automation
- Use GitHub Copilot and AI-assisted engineering tools to improve productivity across scripting, IaC development, CI/CD pipeline creation, code review, troubleshooting, documentation, and automation
- Implement cloud-native solutions using Azure services such as App Service, Azure Functions, Logic Apps, Event Grid, Service Bus, Storage, Key Vault, API Management, Azure SQL, Cosmos DB, Azure Monitor, and Application Insights
- Support the implementation of AI-enabled solutions using Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related Azure AI services
- Build and integrate AI solution components based on patterns such as RAG, agentic workflows, multi-agent orchestration, tool/function calling, prompt management, grounding, evaluation, and responsible AI controls
- Implement secure integration patterns using managed identities, RBAC, private endpoints, private DNS, network security groups, firewalls, and API gateways
- Establish and maintain observability using Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, distributed tracing, and operational runbooks
- Troubleshoot complex cloud, networking, deployment, performance, security, and production incidents
- Apply DevSecOps practices, including secrets management, dependency scanning, container image scanning, policy validation, secure configuration, and compliance automation
- Optimize Azure environments for performance, reliability, scalability, and cost efficiency
- Contribute to technical standards, reusable templates, documentation, operational procedures, and platform engineering practices
- Provide technical guidance, mentoring, code reviews, and engineering leadership to other team members
- Work with architects and stakeholders to translate requirements into practical, secure, and maintainable Azure implementations
