Lead Azure Cloud Engineer

About the Position

We are seeking a seasoned Lead Azure Cloud Engineer to architect, develop, automate, and manage secure, scalable, and cost-effective cloud solutions on Microsoft Azure.

Remote in Poland

Responsibilities

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

Requirements

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

Nice to Have

• Microsoft Azure certifications including Azure Administrator Associate, Azure Developer Associate, Azure DevOps Engineer Expert, or Azure Solutions Architect Expert
• Kubernetes certifications including CKA, CKAD, or CKS
• Experience with production-grade AKS platforms, service mesh, GitOps, Helm, Kustomize, Flux, Argo CD, or Kubernetes policy engines
• Experience with Azure AI Foundry, Semantic Kernel, LangChain, LangGraph, AutoGen, or similar AI orchestration frameworks
• Experience developing or supporting RAG platforms, AI agents, multi-agent workflows, or enterprise knowledge search solutions
• Experience with platform engineering, internal developer platforms, self-service cloud capabilities, paved roads, and reusable engineering templates
• Experience in regulated industries with rigorous compliance, security, auditability, and governance requirements
• Familiarity with SRE practices, incident response, reliability engineering, performance testing, and cost optimization

We Offer

• Opportunity to work remotely from Poland
• Engaging with cutting-edge technologies and frameworks
• Collaborative environment with cross-functional teams
• Professional growth and development opportunities

About the Company

EPAM Systems is a global software engineering and product development company that partners with the world’s leading brands to deliver digital transformation and technology innovation.