Lead Azure Cloud Engineer

We're looking for a seasoned Lead Azure Cloud Engineer to architect, construct, automate, and manage secure, scalable, and cost-effective cloud solutions on Microsoft Azure. This role involves direct engagement with Azure infrastructure, containerization, DevOps pipelines, Infrastructure as Code, observability, security controls, and AI-driven cloud solutions.

You'll help convert architecture standards into functioning platforms, repeatable deployment patterns, automation processes, and production-ready services. You'll partner closely with Cloud Architects, Platform Engineering, DevOps, Security, Networking, Data, AI, and Product teams to deliver strong Azure solutions supporting modern application delivery, containerized workloads, and enterprise AI capabilities.

Responsibilities

Design, implement, and maintain Azure cloud infrastructure, including subscriptions, resource groups, networking, identity, governance, security, and platform services Construct and support reusable Azure deployment patterns for applications, APIs, front-end workloads, microservices, containers, serverless services, data integrations, and AI-enabled solutions Operate and implement Azure Kubernetes Service environments, covering node pools, ingress, workload identity, secrets management, autoscaling, networking, monitoring, container registry integration, and security controls Develop, maintain, and enhance Infrastructure as Code using Terraform, including reusable modules, multi-environment deployments, automated validation, and CI/CD pipeline integration Create and implement CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or comparable tools Support 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 in scripting, IaC development, CI/CD pipeline creation, code review, troubleshooting, documentation, 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 Support implementation of AI-enabled solutions using Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related Azure AI services Construct and integrate AI solution components based on patterns such as RAG, agentic workflows, multi-agent orchestration, tool/function calling, prompt management, grounding, evaluation, and responsible AI controls Implement secure integration patterns leveraging managed identities, RBAC, private endpoints, private DNS, network security groups, firewalls, and API gateways Set up and maintain observability using 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 Apply Dev.

Sec. Ops practices including secrets management, dependency scanning, container image scanning, policy validation, secure configuration, and compliance automation Enhance Azure environments for performance, reliability, scalability, and cost efficiency Contribute to technical standards, reusable templates, documentation, operational procedures, and platform engineering practices Drive adoption of platform standards and reusable templates across teams, measuring adoption and its effect on delivery Lead the Azure engineering team: set technical direction, provide mentoring and code reviews, grow the engineers around you into their next roles, and own the delivery outcomes of the Azure platform Own technical decisions on client engagements, representing architecture and delivery risk to client stakeholders and EPAM leadership, and handling ambiguous requirements with clear trade-offs Requirements Extensive hands-on experience architecting, implementing, and managing Azure cloud solutions within enterprise environments Strong grasp of Azure networking, identity, governance, security, monitoring, and platform services Applied 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 Extensive experience with Terraform or similar Infrastructure as Code tools, including module development, state management, validation, and multi-environment delivery Extensive experience with CI/CD pipelines, ideally using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar platforms Solid grasp of DevOps and Dev.

Sec. Ops practices including automated testing, security scanning, artifact management, release automation, and deployment governance Background working with GitHub, pull requests, code reviews, branching strategies, and collaborative engineering workflows Experience defining how AI-native tools and models are used across engineering teams, including review and verification standards for AI-generated code and infrastructure Background 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 Background implementing observability using Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerting, and operational runbooks Grasp of Azure AI and Generative AI services, particularly Azure OpenAI, Azure AI Search, and AI-enabled automation patterns Experience designing AI architecture patterns such as RAG, agentic workflows and multi-agent systems, and defining evaluation, grounding and responsible AI standards for teams building them Capability to resolve complex technical issues spanning cloud infrastructure, networking, containers, CI/CD, security, and application integration Solid scripting and automation abilities using Power.

Shell, Bash, Python, or comparable languages Proven ability to own delivery outcomes for production Azure environments, including planning capacity and team workload across concurrent work Experience leading or mentoring a team of five or more engineers, including performance management and career development Strong communication skills and capability to collaborate with architects, engineers, security teams, product teams, and business stakeholders Nice to have Microsoft Azure certifications such as Azure Administrator Associate, Azure Developer Associate, Azure DevOps Engineer Expert, or Azure Solutions Architect Expert Kubernetes certifications such as CKA, CKAD, or CKS Background with production-grade AKS platforms, service mesh, Git.

Ops, Helm, Kustomize, Flux, Argo CD, or Kubernetes policy engines Background with Azure AI Foundry, Semantic Kernel, Lang. Chain, Lang. Graph, Auto. Gen, or comparable AI orchestration frameworks Background constructing or supporting RAG platforms, AI agents, multi-agent workflows, or enterprise knowledge search solutions Background with platform engineering, internal developer platforms, self-service cloud capabilities, paved roads, and reusable engineering templates Background working in regulated industries with strong compliance, security, auditability, and governance requirements Familiarity with SRE practices, incident response, reliability engineering, performance testing, and cost optimization Experience running team-level capacity planning or delivery reporting for a multi-team Azure practice Experience setting AI adoption policy for engineering teams, including cost controls, data-handling rules and evaluation of AI tooling