Senior Infrastructure Architect – AI & Cloud Infrastructure

About the Role

Infrastructure Strategy & Architecture

• Develop and maintain enterprise infrastructure architectures that support current and future business and technology requirements, including AI and advanced analytics workloads.
• Define infrastructure standards, reference architectures, and technology roadmaps covering cloud, hybrid cloud, networking, storage, compute, container platforms, and AI infrastructure capabilities.
• Collaborate with architecture, infrastructure, security, data, and digital teams to ensure infrastructure readiness for AI initiatives.
• Evaluate and recommend infrastructure technologies, cloud services, GPU-enabled environments, and platform services that support enterprise AI adoption.
• Ensure infrastructure architectures align with security, governance, operational, and regulatory requirements.

AI & Cloud Infrastructure Enablement

• Design and govern infrastructure platforms supporting AI, Machine Learning, Generative AI, and data-intensive workloads.
• Architect GPU-enabled cloud and on-premises infrastructure to support AI model training, inference, and deployment.
• Design scalable environments supporting Azure AI Services, Azure OpenAI, Azure Machine Learning, AI Foundry, and related AI platforms.
• Define infrastructure requirements for Retrieval-Augmented Generation (RAG), vector databases, AI assistants, and intelligent automation solutions.
• Ensure AI workloads are deployed using enterprise-grade infrastructure, security, networking, and operational standards.

Cloud & Platform Architecture

• Lead the design and implementation of cloud-native infrastructure solutions with a focus on scalability, availability, security, performance, and operational efficiency.
• Drive adoption of Infrastructure as Code (IaC), automation, containerization, and platform engineering best practices.
• Provide technical leadership on Kubernetes, Docker, cloud platforms, and AI infrastructure deployment models.
• Support the evolution of DevSecOps practices to enable automated infrastructure provisioning and operational excellence.

Security, Reliability & Performance

• Design secure infrastructure architectures supporting enterprise applications and AI workloads.
• Implement controls for identity management, network security, data protection, encryption, and workload isolation.
• Define and implement high availability, disaster recovery, backup, and business continuity strategies.
• Monitor infrastructure performance and drive continuous optimization and modernization initiatives.
• Support FinOps practices and cloud cost optimization across infrastructure and AI platforms.

Required

• Bachelor's degree in Computer Science, Information Technology, Information Security, or a related field.
• Minimum 5 years of experience in infrastructure architecture, cloud architecture, or enterprise platform design.
• Hands-on experience with Microsoft Azure cloud services.
• Experience with containerization technologies such as Docker and Kubernetes.
• Proven experience designing and governing enterprise-scale infrastructure solutions.

Preferred

• Master's degree in a relevant discipline.
• TOGAF, Azure Solutions Architect, or equivalent cloud architecture certifications.
• Experience supporting AI, Machine Learning, and Generative AI platforms.

Technical Skills

• Azure Cloud architecture and services.
• Azure AI Services, Azure OpenAI, and Azure Machine Learning.
• Kubernetes and container orchestration.
• Infrastructure as Code (Terraform, Bicep, ARM templates, or equivalent).
• Cloud networking, storage, compute, and virtualization.
• AI platform hosting and operational architecture.
• Infrastructure support for Machine Learning and Generative AI workloads.
• AI security, governance, and compliance.
• DevSecOps, automation, and CI/CD practices.
• FinOps and cloud cost optimization.

Professional Competencies

• Strong analytical and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to manage multiple priorities and work independently.
• Strong planning, organization, and execution skills.
• Collaborative mindset with the ability to influence technical and business stakeholders.