Lead Azure Cloud Engineer

EPAM is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, the company empowers clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• Extensive hands-on experience architecting, deploying, and managing Azure cloud solutions in enterprise environments
• Strong knowledge of Azure networking, identity, governance, security, monitoring, and platform services
• Experience with Azure Landing Zone concepts, hub-and-spoke networking, private endpoints, private DNS, firewalls, NSGs, and route tables
• Deep expertise in Azure Kubernetes Service, containers, container registries, ingress controllers, workload identity, autoscaling, monitoring, and container security
• Proficiency with Infrastructure as Code using Terraform, including module development and multi-environment deployments
• Experience with CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar
• Solid understanding of DevOps and DevSecOps practices including automated testing, security scanning, artifact management, release automation, and deployment governance
• Familiarity with GitHub workflows including pull requests, code reviews, and branching strategies
• Experience with AI-assisted development tools such as GitHub Copilot
• Experience with Azure PaaS and integration services like App Service, Azure Functions, Logic Apps, API Management, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, and Cosmos DB
• Experience deploying observability and monitoring solutions using Azure Monitor, Log Analytics, Application Insights, and operational runbooks
• Knowledge of Azure AI and Generative AI services, notably Azure OpenAI and Azure AI Search
• Working knowledge of AI architecture patterns including RAG, agentic workflows, multi-agent orchestration, function/tool calling, prompt management, evaluation, and responsible AI
• Ability to resolve complex technical issues involving cloud infrastructure, networking, containers, CI/CD, security, and application integration
• Strong scripting and automation skills with PowerShell, Bash, Python, or similar
• Ability to work independently and deliver production-grade cloud solutions
• Excellent communication and collaboration skills with architects, engineers, security, product, and business teams

Nice to have:

• Microsoft Azure certifications (Azure Administrator Associate, Azure Developer Associate, Azure DevOps Engineer Expert, Azure Solutions Architect Expert)
• Kubernetes certifications (CKA, CKAD, CKS)
• Experience with production-grade AKS platforms, service mesh, GitOps, Helm, Kustomize, Flux, Argo CD, and 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 strict compliance, security, auditability, and governance
• Familiarity with SRE practices, incident response, reliability engineering, performance testing, and cost optimization

• 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 applications, APIs, containers, serverless services, data integrations, and AI-driven solutions
• Deploy and manage Azure Kubernetes Service environments covering node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry integration, and security controls
• Create and maintain Infrastructure as Code with Terraform, including reusable modules and CI/CD pipeline 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, rollback strategies, and release automation
• Use AI-assisted tools like GitHub Copilot for scripting, IaC development, code review, troubleshooting, and documentation
• Deploy cloud-native solutions using Azure services such as App Service, Azure Functions, Logic Apps, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, Cosmos DB, Azure Monitor, and Application Insights
• Assist with deploying AI-driven solutions using Azure AI services including Azure OpenAI and Azure Machine Learning
• Develop and integrate AI solution components based on patterns like RAG, agentic workflows, multi-agent orchestration, prompt management, and responsible AI controls
• Implement secure integration patterns with managed identities, RBAC, private endpoints, network security groups, firewalls, and API gateways
• Establish observability via Azure Monitor, Log Analytics, Application Insights, dashboards, alerts, distributed tracing, and operational runbooks
• Resolve complex incidents in cloud infrastructure, networking, deployment, performance, security, and production
• Implement DevSecOps practices including secrets management, dependency and 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 engineering leadership
• Collaborate with architects and stakeholders to translate requirements into secure, maintainable Azure implementations

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