Azure Cloud Engineering Lead: AI-Driven Infra & AKS

EPAM Systems; Turkey; On-site; TRY 5,923,000 - 8,885,000; Full time

Benefits offered by this job

Private health insurance

Mentoring programs

English courses

Certification support

Learning platform access

Extra leave days

Referral bonuses

Job summary

EPAM Systems specializes in AI transformation and platform engineering and seeks a Lead Azure Cloud Engineer to architect, implement, and manage secure, scalable Azure-based infrastructures. You will design Kubernetes-based deployments, IaC patterns, and CI/CD pipelines while collaborating with cross-functional teams on AI-enabled cloud solutions.

The role emphasizes governance, security, observability, and production-grade delivery, with opportunities to mentor engineers and drive architectural

Qualifications

• 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 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 DevSecOps 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.
• Applied experience using GitHub Copilot or comparable AI-assisted development tools for infrastructure, automation, scripting, pipeline development, or documentation.
• 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.
• Applied knowledge of AI architecture patterns such as RAG, agentic workflows, multi-agent systems, tool/function calling, grounding, prompt management, evaluation, and responsible AI
• Capability to resolve complex technical issues spanning cloud infrastructure, networking, containers, CI/CD, security, and application integration.
• Solid scripting and automation abilities using PowerShell, Bash, Python, or comparable languages.
• Capacity to work independently, own technical delivery, and support production-grade cloud environments.
• Strong communication skills and capability to collaborate with architects, engineers, security teams, product teams, and business stakeholders.

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 DevSecOps 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
• Offer technical guidance, mentoring, code reviews, and engineering leadership to team members
• Collaborate with architects and stakeholders to convert requirements into practical, secure, and maintainable Azure implementations

Skills

Azure cloud

Kubernetes

Terraform

CI/CD pipelines

DevSecOps

Automation

PowerShell

Bash

Python

GitHub Copilot

Tools

GitHub Actions

Azure DevOps

GitLab CI/CD

Terraform

Job description

EPAM Systems specializes in AI transformation and platform engineering and seeks a Lead Azure Cloud Engineer to architect, implement, and manage secure, scalable Azure-based infrastructures. You will design Kubernetes-based deployments, IaC patterns, and CI/CD pipelines while collaborating with cross-functional teams on AI-enabled cloud solutions.

The role emphasizes governance, security, observability, and production-grade delivery, with opportunities to mentor engineers and drive architectural