azure engineer

EPAM provides enterprise software products, open source solutions, and technology accelerators. Its teams deliver cloud, AI, platform engineering, and modern application solutions for enterprise clients.

• Design, implement, and maintain Azure cloud infrastructure, including subscriptions, resource groups, networking, identity, governance, security, and platform services;
• Build and support reusable Azure deployment patterns for applications, APIs, front-end workloads, microservices, containers, serverless services, data integrations, and AI-enabled solutions;
• Implement and operate Azure Kubernetes Service environments, including node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry integration, and security controls;
• Build, maintain, and improve Infrastructure as Code using Terraform, including reusable modules, multi-environment deployments, automated validation, and CI/CD integration;
• Design and implement CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar tools;
• Support DevOps practices such as automated builds, testing, security scanning, artifact management, environment promotion, deployment approvals, rollback strategies, and release automation;
• Use GitHub Copilot and AI-assisted engineering tools for scripting, IaC development, CI/CD pipeline creation, code review, troubleshooting, documentation, and automation;
• Implement 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;
• Support AI-enabled solutions using Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related Azure AI services;
• Build and integrate AI solution components based on 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, private DNS, network security groups, firewalls, and API gateways;
• Establish and maintain observability using Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerts, distributed tracing, and operational runbooks;
• Troubleshoot complex cloud, networking, deployment, performance, security, and production incidents;
• Apply DevSecOps practices, including secrets management, dependency scanning, container image scanning, policy validation, secure configuration, 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 to other team members;
• Work with architects and stakeholders to translate requirements into practical, secure, and maintainable Azure implementations.

• Strong hands-on experience designing, implementing, and operating Azure cloud solutions in enterprise environments;
• Solid understanding of Azure networking, identity, governance, security, monitoring, and platform services;
• Practical experience with Azure Landing Zone concepts, hub-and-spoke networking, private endpoints, private DNS, firewalls, NSGs, route tables, and workload integration patterns;
• Strong hands-on experience with Azure Kubernetes Service, containers, container registries, ingress controllers, workload identity, autoscaling, monitoring, and container security;
• Strong experience with Terraform or other Infrastructure as Code tools, including module development, state management, validation, and multi-environment delivery;
• Strong experience with CI/CD pipelines, preferably using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar platforms;
• Good understanding of DevOps and DevSecOps practices, including automated testing, security scanning, artifact management, release automation, and deployment governance;
• Experience working with GitHub, pull requests, code reviews, branching strategies, and collaborative engineering workflows;
• Practical experience using GitHub Copilot or similar AI-assisted development tools for infrastructure, automation, scripting, pipeline development, or documentation;
• 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, and related services;
• Experience implementing observability using Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerting, and operational runbooks;
• Understanding of Azure AI and Generative AI services, especially Azure OpenAI, Azure AI Search, and AI-enabled automation patterns;
• Practical knowledge of AI architecture patterns such as RAG, agentic workflows, multi-agent systems, tool/function calling, grounding, prompt management, evaluation, and responsible AI;
• Ability to troubleshoot complex technical issues across cloud infrastructure, networking, containers, CI/CD, security, and application integration;
• Strong scripting and automation skills using PowerShell, Bash, Python, or similar languages;
• Ability to work independently, take ownership of technical delivery, and support production-grade cloud environments;
• Strong communication skills and ability to work with architects, engineers, security teams, product teams, and business stakeholders;
• Nice to have: Microsoft Azure certifications, Kubernetes certifications, production-grade AKS platforms, service mesh, GitOps, Helm, Kustomize, Flux, Argo CD, Kubernetes policy engines, Azure AI Foundry, Semantic Kernel, LangChain, LangGraph, AutoGen, RAG platforms, AI agents, multi-agent workflows, enterprise knowledge search solutions, platform engineering, internal developer platforms, self-service cloud capabilities, paved roads, reusable engineering templates, regulated industries, SRE practices, incident response, reliability engineering, performance testing, cost optimization.

• No conditions specified