ppWe welcome applications from professionals at all career levels, from Analyst through to Senior Manager. /p pWe are looking for AI Infrastructure Architects at multiple experience levels to design, build, deploy and optimise the infrastructure that powers real-world artificial intelligence and machine learning solutions. This is a hands‑on role spanning cloud, on‑premises and hybrid environments, with work across GPU clusters, distributed training, model serving, data pipelines, CI/CD, InfraOps, MLOps, monitoring and enterprise integration. /p pWhether you are developing your infrastructure engineering skills, leading delivery workstreams, owning complex architecture decisions or setting technical strategy at the practice level, you will help create scalable, secure, cost‑efficient AI/ML infrastructure that delivers measurable business value for clients. /p h3What you will /h3 ul liDesign, build, configure and optimise AI/ML infrastructure across public cloud, on‑premise and hybrid environments. /li liProvision and tune compute resources, including GPU clusters, distributed training environments, networking, storage, orchestration and model‑serving platforms. /li liWrite, review and maintain code, scripts, infrastructure‑as‑code, deployment automation and CI/CD pipelines for reliable AI system releases. /li liDeploy AI systems, machine learning models and data pipelines into production, ensuring performance, reliability, security and compliance. /li liMonitor infrastructure and AI systems across InfraOps and MLOps, including observability, alerting, model performance, drift, cost and resource utilisation. /li liTroubleshoot and resolve issues across the full computational stack, from hardware and networking through software, pipelines and models. /li liEvaluate tools, frameworks, platforms and emerging technologies, advising on where they fit within scalable AI infrastructure solutions. /li liCollaborate with clients, stakeholders, engineers and cross‑functional teams to translate business requirements into practical,



defensible architecture decisions. /li liDocument standards, procedures, design decisions and best practices to support repeatable delivery and knowledge sharing. /li /ul h3What we are looking for /h3 ul liA degree in Computer Science, Computer Engineering or a related engineering field, or equivalent practical experience. /li liStrong understanding of AI, machine learning and the infrastructure required to train, deploy, monitor and operate AI/ML systems. /li liHands‑on experience coding, building, monitoring and troubleshooting AI/ML applications or infrastructure. /li liProgramming capability in languages such as Python, Java or C++, plus scripting and automation skills. /li liExperience with cloud or on‑premises infrastructure, ideally including hyperscaler platforms such as AWS, Azure or Google Cloud. /li liKnowledge of containers, orchestration, model deployment frameworks, CI/CD, infrastructure‑as‑code, monitoring and production operations. /li liExperience with data pipelines and workflow management tools such as Apache Airflow or Kubeflow. /li liStrong problem‑solving, communication and collaboration skills, with the ability to work effectively in fast‑paced, cross‑functional environments. /li /ul h3For more senior levels /h3 ul liProven ability to lead AI/ML infrastructure projects, teams or architecture workstreams from concept through delivery. /li liExperience making and documenting architecture decisions across compute, networking, storage, orchestration, model serving, security, compliance, cost and scalability. /li liDeep expertise in at least one hyperscale platform, with broader awareness of AI/ML services, accelerators, interconnects, performance levers and cost optimisation options. /li liAbility to advise clients and senior stakeholders, translating complex technical trade‑offs into clear recommendations linked to business outcomes. /li liExperience defining architecture standards, reference patterns, roadmaps, governance, observability strategies and best practices for enterprise‑scale AI/ML infrastructure. /li /ul /p #J-18808-Ljbffr

📌 AI Infrastructure Architecture (Barcelona)
🏢 Accenture
📍 Barcelona