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, EPAM 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 settings
• 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, 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, including module development, state management, validation, and multi-environment delivery
• Experience with CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar
• 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, and branching strategies
• Hands-on experience with GitHub Copilot or comparable AI-assisted development tools
• Experience with Azure PaaS and integration services such as App Service, Azure Functions, Logic Apps, API Management, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, Cosmos DB
• Experience deploying observability using Azure Monitor, Log Analytics, Application Insights, and Container Insights
• Knowledge of Azure AI and Generative AI services including Azure OpenAI, Azure AI Search, and AI 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
• Ability to resolve complex issues across cloud infrastructure, networking, containers, CI/CD, security, and application integration
• Strong scripting and automation skills using PowerShell, Bash, Python, or similar
• Ability to work independently and support production-grade cloud environments
• Excellent communication and collaboration skills with cross-functional teams

• 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 various workloads including applications, APIs, microservices, 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, maintain, and enhance Infrastructure as Code using Terraform, including reusable modules and multi-environment deployments
• Architect and deploy CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar tools
• Enable DevOps practices such as automated builds, testing, security scanning, artifact management, deployment approvals, and release automation
• Leverage GitHub Copilot and AI-assisted tools for scripting, IaC development, pipeline creation, code review, troubleshooting, documentation, and automation
• Deploy cloud-native solutions with 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 deploying AI-driven solutions using Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related services
• Develop and integrate AI solution components based on patterns like 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 maintain 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
• Provide technical guidance, mentoring, code reviews, and engineering leadership
• Collaborate with architects and stakeholders to convert requirements into secure and maintainable Azure implementations

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