Lead Azure Cloud Engineer

Description

Lead the architecture, development, automation, and secure operation of scalable Azure cloud platforms. You will design repeatable deployment patterns, build CI/CD and Infrastructure as Code, manage AKS and Azure PaaS workloads, and implement observability, DevSecOps, and cost/performance tuning. You’ll also deploy and integrate AI-driven solutions using Azure AI services and responsible AI architecture patterns.

Quick Facts

• Focus: Azure cloud engineering, automation, security, observability, and AI-enabled platforms

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, data integrations, and AI solutions
• Deploy and manage Azure Kubernetes Service (AKS) environments (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 and deploy CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or comparable tools
• Enable DevOps/DevSecOps practices (automated builds, testing, security scanning, artifact management, environment promotion, approvals, rollback strategies, release automation)
• Use GitHub Copilot and AI-assisted engineering tools for scripting, IaC development, CI/CD pipelines, code review, troubleshooting, documentation, and automation
• Deploy Azure cloud-native solutions (App Service, Azure Functions, Logic Apps, Event Grid, Service Bus, Storage, Key Vault, API Management, Azure SQL, Cosmos DB, Azure Monitor, Application Insights)
• Assist in deploying AI-driven solutions with Azure AI services (Azure OpenAI, Azure AI Search, Azure Machine Learning, etc.)
• Develop and integrate AI solution components (RAG, agentic workflows, multi-agent orchestration, tool/function calling, prompt management, grounding, evaluation, responsible AI controls)
• Implement secure integration patterns (managed identities, RBAC, private endpoints, private DNS, NSGs, firewalls, API gateways)
• Set up and sustain observability (Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, distributed tracing, runbooks)
• Resolve complex cloud, networking, deployment, performance, security, and production incidents
• Implement DevSecOps (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 standards, reusable templates, documentation, and platform engineering procedures
• Provide technical guidance, mentoring, and code reviews
• Collaborate with architects and stakeholders to convert requirements into 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 concepts 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 experience with Terraform or other IaC tools (modules, 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 practices (automated testing, security scanning, artifact management, release automation, deployment governance)
• Experience with GitHub workflows (PRs, code reviews, branching strategies)
• Hands-on experience using GitHub Copilot or comparable AI-assisted development tools
• Experience with Azure PaaS and integration services (App Service, Azure Functions, Logic Apps, API Management, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, Cosmos DB)
• Experience deploying observability with Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, and runbooks
• Knowledge of Azure AI and generative AI services (notably Azure OpenAI and Azure AI Search)
• Working knowledge of AI architecture patterns (RAG, agentic workflows, multi-agent orchestration, tool/function calling, grounding, prompt management, evaluation, responsible AI)
• Capacity to resolve complex technical issues across cloud infrastructure, networking, containers, CI/CD, security, and integration
• Strong scripting/automation skills using PowerShell, Bash, Python, or similar
• Ability to operate independently and own production-grade cloud delivery/support
• Excellent communication and collaboration skills

Benefits

• Career development programs, mentoring, and thought leadership opportunities
• Certification support across major cloud/AI providers (including Azure)
• English classes
• Stable pay and participation in an Employee Stock Purchase Plan with a 15% discount
• Health insurance, multisport, and shopping vouchers
• Referral bonuses up to $2,000
• Hybrid work with a remote option within Poland, plus the chance to work abroad up to 60 days annually
• Business-driven relocation opportunities
• Corporate, social, and well-being events