Our client is a global professional services and technology consultancy.
YOU ARE
As a hands-on Infrastructure Architect, you are an experienced engineer with several years in infrastructure engineering who now takes on more complex, higher-impact work designing and optimizing the AI and machine learning infrastructure that powers real-world applications. Working alongside senior architects and engineers — and increasingly leading your own workstreams — you apply proven skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you architect and optimize infrastructure components, write and review code and deployment scripts, design and tune cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and build and optimize data pipelines that feed AI and ML workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute to architectural decisions, and help establish best practices. This is a hands-on, ownership-driven role where you apply and deepen your expertise across modern tools and platforms — including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring — while making meaningful contributions to infrastructure that enables AI-driven business outcomes.
THE WORK
Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling, setting standards for quality across the team.
Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups, optimizing for performance and utilization.
Design and maintain deployment automation and CI/CD pipelines to support reliable, repeatable releases of AI systems, models, and applications.
Deploy AI systems, models, and data pipelines into production, defining and improving the processes and best practices others follow.
...
AI Infrastructure Architect in East Kilbride employer: Hackajob
Joining Google as a Security Platform Engineer in the UK Public Sector means becoming part of a dynamic and innovative team dedicated to delivering secure private cloud services for critical customers. With a strong emphasis on employee growth, you will have access to cutting-edge technology and collaborative opportunities that foster professional development. The inclusive work culture at Google encourages creativity and teamwork, making it an exceptional employer for those seeking meaningful and impactful work in a supportive environment.
