Azure Systems Architect

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. You will ensure that solutions align with enterprise architecture principles, cloud best practices, security requirements, and modern engineering delivery models. You will 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. The remote work option is available to candidates residing and working within Slovakia. Responsibilities Define and maintain the enterprise Azure architecture, including landing zones, subscription strategy, networking, identity, governance, security, platform services, and workload hosting standardsDesign and standardize reusable cloud patterns for application hosting, APIs, front-end applications, microservices, containerized workloads, serverless workloads, data integrations, and supporting platform servicesDefine architecture patterns for Azure Kubernetes Service, containerized workloads, ingress, service mesh, workload identity, secrets management, container security, scaling, observability, and operational readinessEstablish secure and scalable networking architectures, including hub-and-spoke connectivity, private networking, DNS, firewalls, private endpoints, API gateways, and workload integration patternsDefine and oversee implementation standards for Infrastructure as Code, preferably Terraform, including reusable modules, environment promotion, policy-as-code, and automated compliance controlsDrive DevOps and CI/CD architecture standards, including branching strategies, build and release pipelines, environment separation, quality gates, security scanning, automated testing, and deployment automationPromote 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 automationProduce robust, scalable, and secure cloud-native solutions leveraging Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning, and related Azure AI servicesDesign 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 controlsDefine and oversee AI-enabled solutions for document processing, classification, validation, content generation, knowledge discovery, workflow automation, and enterprise searchDrive integration of AI capabilities into existing enterprise platforms and applications to enhance communication, data processing, automation, productivity, and operational efficiencyEstablish observability, security, compliance, resiliency, and cost-management practices using Azure-native capabilities and enterprise governance frameworksProvide architectural guidance, review solution designs, challenge implementation approaches, and ensure alignment with enterprise standards and target-state architectureCollaborate with product, platform, security, data, and engineering teams to translate business objectives into practical cloud, DevOps, container, and AI architecture decisions Requirements Proven experience designing and implementing enterprise-scale Azure cloud architecturesStrong expertise in Azure networking, identity management, governance, security, landing zones, platform services, and workload hosting modelsDeep understanding of Azure Landing Zones, hub-and-spoke network architectures, private connectivity, DNS, firewalls, private endpoints, and workload integration patternsHands-on experience with Azure Kubernetes Service, containers, microservices, container registries, ingress controllers, workload identity, autoscaling, and container platform operationsExperience designing serverless architectures using services such as Azure Functions, Logic Apps, Event Grid, Service Bus, API Management, and related integration servicesHands-on experience with Infrastructure as Code, preferably Terraform, including reusable modules, multi-environment deployments, and integration with CI/CD pipelinesStrong experience designing cloud deployment models and working closely with DevOps teams on CI/CD, automated testing, security scanning, deployment automation, release governance, and operational handoverPractical understanding of GitHub, GitHub Actions, Azure DevOps, GitHub Copilot, and AI-assisted engineering workflows2+ years of experience architecting, deploying, or governing solutions with AI/Generative AI technologies, specifically Azure AI, Azure OpenAI, Azure AI Search, or agent-based workloadsExperience designing AI solution architectures using patterns such as RAG, agentic workflows, multi-agent systems, prompt orchestration, AI evaluation, grounding, guardrails, and responsible AIExperience implementing observability solutions using Azure Monitor, Application Insights, Log Analytics, Container Insights, distributed tracing, dashboards, and alertingKnowledge of Azure cost management, FinOps, capacity planning, and cost optimization practicesStrong understanding of cloud security, DevSecOps, secrets management, managed identities, RBAC, policy enforcement, and compliance-by-designStrong stakeholder management, communication, documentation, and cross-functional collaboration skillsAbility to operate at both strategic and hands-on architecture levels, from enterprise standards to practical implementation guidance Nice to have Microsoft Azure certifications, especially Azure Solutions Architect ExpertKubernetes certifications or strong practical experience with production-grade Kubernetes platformsExperience working in regulated industries with strong compliance, auditability, governance, and data protection requirementsFamiliarity with Azure API Management, event-driven architectures, microservices, and integration platformsExperience with Azure AI Foundry, Semantic Kernel, LangChain, LangGraph, AutoGen, or similar AI orchestration frameworksExperience designing AI platforms with agent registries, tool catalogs, model gateways, prompt/version management, evaluation pipelines, and AI observabilityExperience with platform engineering, internal developer platforms, golden paths, reusable templates, and self-service cloud capabilitiesFamiliarity with SRE practices, reliability engineering, chaos testing, performance testing, and production readiness reviews We offer Opportunity to work in a fast-paced, agile, software engineering cultureBenefit program (5 weeks of vacation, 5 paid sick days, meal vouchers, cafeteria and recreation bonuses, reimbursement of glasses, contribution to pension fund)Referral bonuses for recommended candidatesEnglish language coursesGreat learning and development opportunities, including in-house professional training, career advisory and coaching, sponsored professional certifications, well-being programs, LinkedIn Learning Solutions and much more Certain benefits and perks may be subject to eligibility requirements and may be available only after you have passed your probationary period.