Enterprise Architect - Data, AI & Platforms

The Enterprise Architect – Data, AI & Platforms is a senior leader within the Enterprise Architecture function, responsible for defining, governing, and evolving the organization’s end‑to‑end technology architecture across data, AI/ML, platforms, and infrastructure. This role ensures that the enterprise technology landscape is modern, scalable, secure, cloud‑ready, and optimized to enable data‑driven decision-making, intelligent automation, and digital transformation. The Enterprise Architect partners with data teams, infrastructure, application development, security, and business domain architects to design an integrated technology ecosystem that accelerates value creation and supports enterprise strategic priorities.

Responsibilities:

• Define and maintain the enterprise target architecture across data, AI, platforms, and infrastructure, including principles, standards, patterns, and reference architectures.
• Establish architecture guardrails that promote data quality, AI readiness, platform automation, integration, standardization, and security by design.
• Lead the development of data and AI platform architecture, covering data lakes, data warehouses, real‑time streaming, ML platforms, and model lifecycle management.
• Drive modernization initiatives across cloud, hybrid, and on‑prem environments to support advanced analytics, AI workloads, and scalable digital platforms.
• Architect solutions that support large-scale analytics, ML training and inference, model deployment, and intelligent automation.
• Collaborate with data architects and engineers to ensure data platforms are highly available, resilient, governed, and optimized for performance and cost.
• Design platform capabilities that streamline DevOps, MLOps, DataOps, observability, and automation.
• Ensure technology decisions support regulatory compliance for data governance, security, privacy, and data residency.
• Lead the evolution of enterprise infrastructure to ensure it meets requirements for scalability, performance, AI compute, storage modernization, network reliability, and cybersecurity.
• Oversee the lifecycle of key platforms including virtualization, container platforms (e.g., OpenShift/Kubernetes), cloud services, storage, and enterprise databases.
• Guide the selection and implementation of infrastructure and cloud technologies that support AI acceleration, distributed computing, and modern data workloads.
• Develop strategies for capacity planning, business continuity, and disaster recovery for critical platforms.
• Partner with business and technology stakeholders to translate business outcomes into capable, scalable, and future-proof technology architectures.
• Lead cross-functional architecture reviews and ensure alignment with enterprise architecture roadmaps.
• Provide technical leadership and mentorship to architects, engineers, and project teams.
• Maintain comprehensive documentation including roadmaps, reference architecture, standards, and guidelines.

Requirements:

• Bachelor’s degree in Computer Science, Information Technology, or related field (or equivalent experience).
• 15+ years in infrastructure, data, or platform engineering/operations, with 5–7 years in architecture leadership roles.
• Demonstrated experience defining enterprise-wide data, AI, platform, and infrastructure architectures in complex hybrid environments.
• Deep expertise in:
• Enterprise data platforms, data engineering, analytics platforms.
• AI/ML platforms, model lifecycle technologies, MLOps.
• Cloud architecture (Azure, OCI, AWS).
• Container platforms (Kubernetes, OpenShift).
• Compute, storage, networking, security, and virtualization technologies.
• Familiarity with infrastructure and platform solutions such as AIX, RHEL, Oracle Database, Dell EMC Storage, Pure Storage, Data Domain, Cisco, Palo Alto, Checkpoint.
• Experience with DevOps, Platform Engineering, DataOps, MLOps, and observability tools.
• Hands-on experience with Infrastructure-as-Code (IaC) and automation tools (Terraform, Ansible, Jenkins, etc.).
• Strong understanding of security architecture, cloud governance, and regulatory requirements.
• Proven ability to lead large-scale platform, data, or infrastructure transformation initiatives.
• Excellent communication, analytical thinking, and cross-functional leadership skills.
• Certifications in cloud, networking, infrastructure, or architecture frameworks (AWS, Azure, TOGAF) are a plus.
• Experience with ITIL, Agile, and modern delivery methodologies.