AI Infrastructure Principal Architect

Salary: £50,000 - 75,000 per year

Requirements:

• Bachelors degree in Computer Science, Computer Engineering, or a related engineering field.
• Significant experience coding, building, monitoring, and troubleshooting AI/ML applications, including selecting, designing, and deploying infrastructure for on-premises or public cloud environments.
• Strong understanding of artificial intelligence and machine learning.
• Strong understanding of computing infrastructure, with preferred knowledge of AI infrastructure.
• Proven experience in programming languages such as Python, Java, or C++.
• Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Excellent communication and collaboration skills.
• Longstanding experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large-scale solutions.
• Proven experience leading and managing AI projects and teams.
• Strong project management skills with the ability to manage multiple projects simultaneously.
• Demonstrated experience evaluating and selecting AI technologies and frameworks.
• Ability to work with cross-functional teams and drive project alignment.

Responsibilities:

• Set the overarching technical vision and strategy for compute infrastructure supporting large-scale AI/ML systems.
• Own complex architecture decisions across compute, networking, storage, orchestration, and model serving.
• Architect and hands-on prototype large-scale, cost-optimized compute and distributed training systems.
• Define reference architectures, standards, and architectural patterns that scale across engagements.
• Personally implement foundational tooling, infrastructure-as-code, and automation.
• Lead enterprise-scale architecture assessments and design reviews.
• Validate findings in the environment, profile real workloads, and demonstrate optimization opportunities.
• Shape and steward the AI infrastructure roadmap and technology strategy.
• Identify, evaluate, and hands-on pilot emerging technologies and innovations.
• Drive performance and cost optimization of the computational stack.
• Profile GPU and compute utilization, tune distributed training and model-serving workloads, and engineer improvements to meet SLAs while controlling cost.
• Serve as the principal authority across hyperscaler cloud platforms.
• Lead deep troubleshooting and root-cause analysis across hardware, networking, software, and models.
• Cultivate and lead relationships with infrastructure partners and partnering organizations.
• Provide executive- and client-level technical advisory and translate infrastructure trade-offs into clear recommendations tied to business outcomes.
• Define monitoring, observability, and reliability strategy across InfraOps and MLOps.
• Implement instrumentation, SLAs, SLOs, and cost/performance governance for production AI/ML systems.
• Ensure enterprise integration, security, compliance, and regulatory alignment of AI/ML infrastructure.
• Mentor, elevate, and grow the architect community through pairing, design collaboration, and code/architecture reviews.
• Champion cost-efficiency and value realization for the organizations we serve.

Technologies:

• AI
• Airflow
• Architect
• Cloud
• Hardware
• Java
• Kubeflow
• Machine Learning
• MLOps
• Model Serving
• Python
• Security

More:

We are Accenture, a leading global professional services company helping leading businesses, governments, and other organizations build their digital core, optimize operations, accelerate revenue growth, and enhance citizen services. We are a talent- and innovation-led organization with approximately 791,000 people serving clients in more than 120 countries, and technology is at the core of our work. We combine deep capabilities in cloud, data, and AI with strong ecosystem relationships, global delivery capability, and broad services across Strategy & Consulting, Technology, Operations, Industry X, and Song. This is a full-time role based in London, Paris, Berlin, or Madrid (Castellana 85). We are committed to equal employment opportunity and value the diversity that helps us better serve our clients and communities.

last updated 34 week of 2026