Lead Azure Cloud Engineer

Quick Facts

• Architect, develop, automate, and manage secure, scalable, and cost-effective cloud solutions on Microsoft Azure
• Own Azure infrastructure, AKS platforms, CI/CD, Infrastructure as Code, observability, and DevSecOps
• Work with Azure PaaS integrations and AI-driven solutions (Azure OpenAI, Azure AI Search)

Description

Lead the architecture, deployment, and automation of secure, scalable, and cost-effective cloud solutions on Microsoft Azure. You will work across Azure infrastructure, containers, DevOps pipelines, Infrastructure as Code, observability, security controls, and AI-driven cloud solutions. You will convert architecture standards into repeatable deployment patterns and production-ready services.

Responsibilities

• Architect, deploy, and manage Azure infrastructure (subscriptions, resource groups, networking, identity, governance, security, platform services)
• Develop repeatable Azure deployment patterns for applications, APIs, microservices, containers, serverless services, data integrations, and AI-driven solutions
• Deploy and manage Azure Kubernetes Service (node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry integration, security controls)
• Create and enhance Infrastructure as Code with Terraform (reusable modules, multi-environment deployments, automated validation, CI/CD pipeline integration)
• Architect CI/CD pipelines with GitHub Actions, Azure DevOps, GitLab CI/CD, or comparable tools
• Enable DevOps/DevSecOps practices (automated builds/testing, security scanning, artifact management, approvals, rollback strategies, release automation)
• Use GitHub Copilot and AI-assisted tools for scripting, IaC, pipeline creation, code review, troubleshooting, documentation, and automation
• Deploy cloud-native solutions using Azure PaaS services (App Service, Azure Functions, Logic Apps, Event Grid, Service Bus, Storage, Key Vault, API Management, Azure SQL, Cosmos DB, Azure Monitor, Application Insights)
• Assist with AI-driven solutions using Azure AI (Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning)
• Build AI solution components and patterns (RAG, agentic workflows, multi-agent orchestration, tool/function calling, prompt management, grounding, evaluation, responsible AI)
• Implement secure integration patterns (managed identities, RBAC, private endpoints, private DNS, NSGs, firewalls, API gateways)
• Set up observability with Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, distributed tracing, and operational runbooks
• Resolve complex production incidents across cloud, networking, deployments, performance, security, and application integration
• Implement DevSecOps controls (secrets management, dependency scanning, container image scanning, policy validation, secure configuration, compliance automation)
• Tune Azure environments for performance, reliability, scalability, and cost efficiency
• Contribute to technical standards, templates, documentation, and platform engineering practices; provide mentoring and engineering leadership
• Collaborate with architects and stakeholders to deliver practical, secure, and maintainable Azure implementations

Requirements

• Extensive hands-on experience architecting, deploying, and managing enterprise Azure cloud solutions
• Sound knowledge of Azure networking, identity, governance, security, monitoring, and platform services
• Hands-on experience with Azure Landing Zone and hub-and-spoke networking (private endpoints, private DNS, firewalls, NSGs, route tables)
• Extensive hands-on experience with AKS, containers, container registries, ingress controllers, workload identity, autoscaling, monitoring, and container security
• Substantial Terraform experience (module development, state management, validation, multi-environment delivery)
• Substantial experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI/CD, or similar)
• Solid grasp of DevOps and DevSecOps (automated testing, security scanning, artifact management, release automation, deployment governance)
• Experience with GitHub workflows (pull requests, code reviews, branching strategies)
• Hands-on experience with GitHub Copilot or comparable AI-assisted development tools
• Experience with Azure PaaS and integration services (App Service, Functions, Logic Apps, API Management, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, Cosmos DB)
• Experience with Azure observability (Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, runbooks)
• Knowledge of Azure AI and generative AI services (Azure OpenAI, Azure AI Search)
• Working knowledge of AI architecture patterns (RAG, agentic workflows, multi-agent systems, tool/function calling, grounding, prompt management, evaluation, responsible AI)
• Ability to resolve complex technical issues across cloud infrastructure, networking, containers, CI/CD, security, and application integration
• Strong scripting and automation using PowerShell, Bash, Python, or similar
• Ability to operate independently and own technical delivery for production-grade cloud environments
• Excellent communication and collaboration with architects, engineers, security, product teams, and stakeholders

Benefits

• Hybrid work in Poland with remote opportunity
• Opportunity to work abroad for up to 60 days annually; relocation opportunities
• Career development programs, mentoring, and soft skills and well-being programs
• Certification support (including Azure) and English classes
• Stable pay; Employee Stock Purchase Plan with a 15% discount
• Benefits package (health insurance, multisport, shopping vouchers); referral bonuses up to $2,000
• Office events and social/well-being programs, plus entertainment and relaxation zones