Senior Cloud Solution Architect (Azure)

We are seeking a Senior Cloud Solution Architect (Azure) to design and lead secure, scalable, resilient, and cost-effective cloud and AI solutions using Microsoft Azure. The role will collaborate with business and technology teams to translate business requirements into effective cloud architectures. The ideal candidate will have strong expertise in Azure architecture, cloud modernization, security, networking, DevOps, integration, and automation, as well as hands-on experience architecting and operationalizing AI and generative AI workloads on Azure. They will bring proven experience leading complex cloud transformation initiatives from strategy through implementation. Responsibilities • Cloud architecture and solution design • Design scalable, secure, resilient, and cost-effective Azure cloud architectures aligned with business and technical requirements. • Define architecture standards, patterns, roadmaps, and technical designs across IaaS, PaaS, SaaS, and hybrid environments. • Conduct architecture reviews and ensure alignment with enterprise standards. 2. Azure infrastructure and cloud migration • Architect Azure infrastructure across compute, networking, storage, databases, containers, and integration services. • Lead cloud migration and application modernization initiatives, including strategy, planning, and execution. • Identify technical risks, dependencies, and opportunities for Azure-native modernization. 3. Security, networking and compliance • Design secure Azure solutions incorporating Zero Trust, identity, access management, encryption, and network security. • Architect hybrid connectivity using VNets, VPN, ExpressRoute, Azure Firewall, and related services. • Secure AI services using private endpoints, managed identities, network isolation, and data protection controls aligned with regulatory and data residency requirements. • Ensure solutions meet organizational security, compliance, and governance requirements. 4. DevOps, automation and integration • Define and implement DevOps, CI/CD, DevSecOps, and Infrastructure as Code (IaC) practices. • Promote automation using tools such as Terraform, Bicep, and ARM templates. • Design scalable data, API, integration, and event-driven solutions using Azure services. 5. AI and generative AI workloads • Design and implement enterprise-grade AI solutions on Azure, including generative AI, retrieval-augmented generation (RAG), AI agents, and machine learning workloads. • Architect AI platforms using Microsoft Foundry (formerly Azure AI Foundry), Azure OpenAI, Azure AI Search, Azure Machine Learning, and Azure AI Services. • Design data pipelines, vector search, and grounding strategies that connect AI models securely to enterprise data. • Define MLOps and LLMOps practices covering model deployment, versioning, evaluation, monitoring, and lifecycle management. • Plan and optimize AI infrastructure, including GPU compute, AKS GPU node pools, model hosting options, and capacity models such as Provisioned Throughput Units (PTUs). • Establish Responsible AI, AI governance, and AI security practices, including content safety, data privacy, prompt injection mitigation, and model access controls. 6. Performance, reliability and cost optimization • Design solutions for high availability, disaster recovery, business continuity, and operational resilience. • Establish monitoring, observability, performance, and capacity management practices. • Drive Azure cost optimization and FinOps initiatives to improve cloud efficiency. • Optimize AI workload cost and performance, including token consumption, model selection, caching, and quota and capacity management. 7. Technical leadership and governance • Lead architecture initiatives and collaborate with business stakeholders, engineering, security, DevOps, and vendors. • Conduct architecture workshops, design reviews, and technical decision-making sessions. • Advise stakeholders on AI use case feasibility, solution patterns, and adoption roadmaps. • Establish cloud governance, standards, documentation, and reusable architecture patterns while mentoring technical teams. Required qualifications and experience • Bachelor's degree in IT, Computer Science, Engineering, or a related field. • 10+ years of IT and cloud experience, including 5+ years of hands-on Azure experience and 2+ years designing or delivering AI/ML or generative AI solutions. • Strong expertise in Azure architecture, infrastructure, networking, security, and integration. • Proven experience in cloud migration, application modernization, and enterprise-scale solutions. • Proven experience designing and deploying AI/ML or generative AI solutions in production on Azure, ideally at enterprise scale. • Strong knowledge of DevOps, CI/CD, Infrastructure as Code, and cloud governance. • Excellent communication, stakeholder management, problem-solving, and technical leadership skills. • Microsoft Certified: Azure Solutions Architect Expert. • Microsoft Certified: Azure AI Engineer Associate (AI-102) or equivalent AI certification. • Experience with Microsoft Fabric, Azure Databricks, or similar data platforms supporting AI workloads. Technical skills • Azure: VMs, AKS, App Services, Functions, Storage, Azure SQL, Cosmos DB, Key Vault, API Management, Service Bus, Event Hubs. • AI and machine learning: Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure AI Services (e.g., Document Intelligence, Language, Vision), AI Content Safety, RAG, AI agents, vector databases (e.g., Cosmos DB vector search), prompt engineering, MLOps/LLMOps, and GPU-based compute. • Cloud architecture: Cloud-native, microservices, serverless, event-driven, hybrid cloud, high availability, and disaster recovery. • Security: Microsoft Entra ID, RBAC, Zero Trust, encryption, Key Vault, network security, and AI security controls. • DevOps and automation: Azure DevOps, GitHub Actions, CI/CD, Terraform, Bicep, ARM, containers, and Kubernetes. • Networking: VNets, VPN, ExpressRoute, DNS, NSGs, routing, firewalls, and load balancing. • Monitoring and observability: Azure Monitor, Log Analytics, Application Insights, logging, alerting, and AI model monitoring and evaluation. What we offer • Opportunity to lead enterprise-scale Azure cloud and AI transformation initiatives. • Exposure to modern cloud, AI, DevOps, automation, security, and cloud-native technologies. • Opportunities for career growth, technical leadership, and professional certifications. • Collaboration with senior business and technology stakeholders across the organization. • A collaborative and innovative work environment that values continuous learning. • Opportunity to make a meaningful impact on cloud strategy, AI adoption, and digital transformation. Show more