About this role
Salary: £50,000 - 75,000 per year
Requirements: Bachelors degree in Computer Science, Computer Engineering, or a related Engineering fieldSolid background in coding, building, monitoring, and troubleshooting AI/ML model applications, including selecting, designing, and implementing infrastructure for deployment on premises or in public cloudStrong understanding of AI and machine learningStrong understanding of computing infrastructure, with preferred knowledge of AI infrastructureGood proficiency in programming languages such as Python, Java, or C++Experience with data pipeline and workflow management tools such as Apache Airflow or KubeflowStrong problem-solving skills and ability to work in a fast-paced environmentExcellent communication and collaboration skillsSignificant experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large-scale solutionsProven experience leading and managing AI projects and teamsStrong project management skills, including the ability to manage multiple projects simultaneouslyDemonstrated experience evaluating and selecting AI technologies and frameworksAbility to work with cross-functional teams and drive project alignment Responsibilities: Own the end-to-end architecture and design of optimized compute infrastructure for large-scale AI/ML systems, including large-scale distributed training environments, from concept through deliveryDevelop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, and model serving to make rational, well-justified decisions tailored to each clients situation and standardsLead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks, and optimization opportunities, and recommending remediationDrive architectural decision-making, documenting rationale, trade-offs, and assumptions so decisions are transparent, defensible, and aligned with business SLAs and standardsDefine and maintain the AI infrastructure roadmap, planning capacity, scaling, and technology evolution in step with business and product goalsArchitect and optimize the full computational stack for performance, power, cost, and scalability, ensuring infrastructure meets business SLAs while being deliberately engineered for cost-efficiencyDesign and tune large-scale GPU clusters and distributed training systems, including accelerator selection, interconnect/networking, and storage for high-throughput training workloadsServe as the authoritative AI infrastructure expert in at least one hyperscaler cloud (AWS, Azure, or GCP), applying deep knowledge of its AI/ML services, accelerators, networking, and cost leversDesign deployment, automation, and CI/CD strategies for reliable, repeatable, and scalable releases of AI systems, models, and data pipelines into productionEstablish AI monitoring and observability strategy across InfraOps and MLOps, defining SLAs, SLOs, alerting, and performance/cost tracking, and driving continuous optimizationIntegrate AI/ML systems into enterprise environments, ensuring interoperability, security, compliance, and adherence to regulatory and client standardsLead capacity planning and cost modeling, forecasting compute needs and engineering cost-efficiency into the architecture without compromising performanceCollaborate with clients, stakeholders, and engineering teams to align infrastructure decisions with business outcomes, translating requirements into actionable architecture and standardsSet technical direction, standards, and best practices, mentoring engineers and architects and leading design and code reviews across the team Technologies: AIAirflowAWSArchitectAzureCI/CDCloudGCPJavaKubeflowMachine LearningMLOpsModel ServingPythonSecurity More:
We are Accenture, a leading global professional services company helping the worlds leading businesses, governments, and organizations build their digital core, optimize operations, accelerate revenue growth, and enhance citizen services. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of our work, and we are a leader in cloud, data, and AI with strong ecosystem relationships and global delivery capability. This is a full-time role based in London, Paris, Berlin, or Madrid (Castellana 85). We are committed to shared success, creating 360 value for our clients, our people, our shareholders, partners, and communities, and we value diversity and equal opportunity.
last updated 36 week of 2026