[Hiring] Azure Systems Architect @EPAM Systems

Role Description

We are seeking an experienced Azure Systems Architect to lead the design, governance, and implementation of scalable, secure, cost-efficient, and AI-ready cloud solutions on Microsoft Azure.

In this role, you will:

• Define Azure hosting patterns, networking, security, governance, platform integration standards, container platform architecture, DevOps practices, and AI solution patterns.
• Ensure that solutions align with enterprise architecture principles, cloud best practices, security requirements, and modern engineering delivery models.
• Work closely with Platform Engineering, DevOps, Security, Networking, Data, AI, and Product teams to establish a robust Azure foundation that enables scalable application delivery, operational excellence, and the adoption of AI-enabled engineering and business capabilities.

Qualifications

• Proven experience designing and implementing enterprise-scale Azure cloud architectures.
• Strong expertise in Azure networking, identity management, governance, security, landing zones, platform services, and workload hosting models.
• Deep understanding of Azure Landing Zones, hub-and-spoke network architectures, private connectivity, DNS, firewalls, private endpoints, and workload integration patterns.
• Hands-on experience with Azure Kubernetes Service, containers, microservices, container registries, ingress controllers, workload identity, autoscaling, and container platform operations.
• Experience designing serverless architectures using services such as Azure Functions, Logic Apps, Event Grid, Service Bus, API Management, and related integration services.
• Hands-on experience with Infrastructure as Code, preferably Terraform, including reusable modules, multi-environment deployments, and integration with CI/CD pipelines.
• Strong experience designing cloud deployment models and working closely with DevOps teams on CI/CD, automated testing, security scanning, deployment automation, release governance, and operational handover.
• Practical understanding of GitHub, GitHub Actions, Azure DevOps, GitHub Copilot, and AI-assisted engineering workflows.
• 2+ years of experience architecting, deploying, or governing solutions with AI/Generative AI technologies, specifically Azure AI, Azure OpenAI, Azure AI Search, or agent-based workloads.
• Experience designing AI solution architectures using patterns such as RAG, agentic workflows, multi-agent systems, prompt orchestration, AI evaluation, grounding, guardrails, and responsible AI.
• Experience implementing observability solutions using Azure Monitor, Application Insights, Log Analytics, Container Insights, distributed tracing, dashboards, and alerting.
• Knowledge of Azure cost management, FinOps, capacity planning, and cost optimization practices.
• Strong understanding of cloud security, DevSecOps, secrets management, managed identities, RBAC, policy enforcement, and compliance-by-design.
• Strong stakeholder management, communication, documentation, and cross-functional collaboration skills.
• Ability to operate at both strategic and hands-on architecture levels, from enterprise standards to practical implementation guidance.

Requirements

• Define and maintain the enterprise Azure architecture, including landing zones, subscription strategy, networking, identity, governance, security, platform services, and workload hosting standards.
• Design and standardize reusable cloud patterns for application hosting, APIs, front-end applications, microservices, containerized workloads, serverless workloads, data integrations, and supporting platform services.
• Define architecture patterns for Azure Kubernetes Service, containerized workloads, ingress, service mesh, workload identity, secrets management, container security, scaling, observability, and operational readiness.
• Establish secure and scalable networking architectures, including hub-and-spoke connectivity, private networking, DNS, firewalls, private endpoints, API gateways, and workload integration patterns.
• Define and oversee implementation standards for Infrastructure as Code, preferably Terraform, including reusable modules, environment promotion, policy-as-code, and automated compliance controls.
• Drive DevOps and CI/CD architecture standards, including branching strategies, build and release pipelines, environment separation, quality gates, security scanning, automated testing, and deployment automation.
• Promote modern engineering practices using GitHub, GitHub Actions, Azure DevOps, GitHub Copilot, and AI-assisted software delivery, including AI-supported CI/CD, code review, documentation, testing, and platform automation.
• Produce robust, scalable, and secure cloud-native solutions leveraging Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related Azure AI services.
• Design AI-enabled solutions based on modern patterns such as RAG, agentic workflows, multi-agent architectures, AI orchestration, tool/function calling, prompt management, evaluation, grounding, guardrails, and responsible AI controls.
• Define and oversee AI-enabled solutions for document processing, classification, validation, content generation, knowledge discovery, workflow automation, and enterprise search.
• Drive integration of AI capabilities into existing enterprise platforms and applications to enhance communication, data processing, automation, productivity, and operational efficiency.
• Establish observability, security, compliance, resiliency, and cost-management practices using Azure-native capabilities and enterprise governance frameworks.
• Provide architectural guidance, review solution designs, challenge implementation approaches, and ensure alignment with enterprise standards and target-state architecture.
• Collaborate with product, platform, security, data, and engineering teams to translate business objectives into practical cloud, DevOps, container, and AI architecture decisions.

Benefits

• Microsoft Azure certifications, especially Azure Solutions Architect Expert.
• Kubernetes certifications or strong practical experience with production-grade Kubernetes platforms.
• Experience working in regulated industries with strong compliance, auditability, governance, and data protection requirements.
• Familiarity with Azure API Management, event-driven architectures, microservices, and integration platforms.
• Experience with Azure AI Foundry, Semantic Kernel, LangChain, LangGraph, AutoGen, or similar AI orchestration frameworks.
• Experience designing AI platforms with agent registries, tool catalogs, model gateways, prompt/version management, evaluation pipelines, and AI observability.
• Experience with platform engineering, internal developer platforms, golden paths, reusable templates, and self-service cloud capabilities.
• Familiarity with SRE practices, reliability engineering, chaos testing, performance testing, and production readiness reviews.