Lead Azure Cloud Engineer

EPAM is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and startups. It has over thirty years of expertise in custom software, product, and platform engineering enabling clients to become AI-Native enterprises.

• Extensive experience architecting, deploying, and managing Azure cloud solutions in enterprise environments
• Strong 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 integrations
• Extensive experience with Azure Kubernetes Service, containers, registries, ingress controllers, workload identity, autoscaling, monitoring, and container security
• Proficient with Infrastructure as Code tools, primarily Terraform, including module development, state management, validation, and multi-environment delivery
• Experienced with CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or equivalent
• Solid understanding of DevOps and DevSecOps practices including automated testing, security scanning, artifact management, release automation, and deployment governance
• Familiar with GitHub, pull requests, code reviews, branching strategies, and collaborative workflows
• Experience using AI-assisted tools like GitHub Copilot for infrastructure automation, scripting, pipeline development, code reviews, and 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
• Skilled in deploying observability solutions using Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerting, and operational runbooks
• Knowledgeable about Azure AI and Generative AI services, including Azure OpenAI, Azure AI Search, and AI automation patterns
• Working knowledge of AI architecture patterns such as RAG, agentic workflows, multi-agent systems, tool/function calling, grounding, prompt management, evaluation, and responsible AI
• Able to resolve complex technical issues in cloud infrastructure, networking, containers, CI/CD, security, and integration
• Strong scripting and automation skills with PowerShell, Bash, Python, or similar
• Ability to operate independently with ownership of technical delivery and production-grade cloud environments
• Excellent communication and collaboration skills with architects, engineers, security teams, product teams, and business stakeholders

• Architect, deploy, and manage Azure cloud infrastructure including subscriptions, resource groups, networking, identity, governance, security, and platform services
• Develop and maintain repeatable Azure deployment patterns for diverse workloads including applications, APIs, microservices, containers, serverless services, data integrations, and AI solutions
• Deploy and manage Azure Kubernetes Service environments with node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry, and security controls
• Create and enhance Infrastructure as Code using Terraform, including reusable modules, multi-environment deployments, validation, and CI/CD integration
• Architect and deploy CI/CD pipelines with GitHub Actions, Azure DevOps, GitLab CI/CD, or similar tools
• Enable DevOps practices including automated builds, testing, security scanning, artifact management, deployment approvals, and rollback strategies
• Use AI-assisted tools like GitHub Copilot to improve productivity in scripting, IaC, code review, troubleshooting, and automation
• Deploy 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
• Assist in deploying AI-driven solutions with Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related services
• Develop AI solution components based on patterns like 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, DNS, network security groups, firewalls, and API gateways
• Set up observability with Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, tracing, and operational runbooks
• Resolve complex incidents related to cloud, networking, deployment, performance, security, and production
• Implement DevSecOps practices including secrets management, dependency scanning, container image scanning, policy validation, 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 leadership to team members
• Collaborate with architects and stakeholders to transform requirements into secure and maintainable Azure implementations

Klikając w przycisk „Aplikuj” lub w inny sposób wysyłając zgłoszenie rekrutacyjne, zgadzasz się na przetwarzanie Twoich danych osobowych przez EPAM Systems (Poland) sp. z o.o. z siedzibą w: Fabryczna 1A, 31-553 Kraków (Pracodawca), jako administratora danych osobowych w celu przeprowadzenia rekrutacji na stanowisko wskazane w ogłoszeniu zgodnie Polityką Prywatności.