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# AI Infrastructure Architect

- **Company:** Accenture
- **Location:** London, UK
- **Salary:** £35,000.0 - £52,500.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, C++ (Programming Language), Cloud Computing, Computer Clusters, Code Review, Computer Engineering, Continuous Integration, Software Debugging, Interoperability, Python (Programming Language), Machine Learning, Release Management, Workflow Management Systems, AI Infrastructure, Kubernetes, Information Technology, Deployment Automation, Machine Learning Operations, Data Pipelines, Docker
- **Published:** August 27, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5856705425

## About the Role

* Bachelors degree in Computer Science, Computer Engineering, or a related engineering field.
 * Practical experience coding, building, monitoring, and troubleshooting AI/ML model applications.
 * Experience selecting, designing, and implementing infrastructure for deploying and running AI/ML solutions on-premises or in public cloud environments.
 * Strong understanding of AI and machine learning.
 * Strong understanding of computing infrastructure, with preferred knowledge of AI infrastructure.
 * Proficiency 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.
 * Proven experience in AI/ML infrastructure engineering or a related role on a hyperscaler platform for large-scale deployments.

## Description

* Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling.
 * Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.
 * Design and maintain deployment automation and CI/CD pipelines for reliable AI system, model, and application releases.
 * Deploy AI systems, models, and data pipelines into production and improve the processes and best practices used by others.
 * Lead container orchestration and model serving using tools such as Docker, Kubernetes, and model deployment frameworks.
 * Optimize the computational stack for performance, power, cost, and scalability.
 * Evaluate and select tools, frameworks, and platforms and make recommendations that shape the infrastructure roadmap.
 * Integrate AI models and systems into existing enterprise systems while ensuring interoperability, security, and regulatory compliance.
 * Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization.
 * Independently troubleshoot and resolve complex issues across hardware, networking, software, and models, and lead root-cause analysis.
 * Mentor junior engineers and lead code reviews.
 * Define and document architecture standards, processes, and procedures, applying security, cost-efficiency, and scalability best practices.

Technologies:

 * AI
 * Airflow
 * Architect
 * CI/CD
 * Cloud
 * Docker
 * Hardware
 * Java
 * Kubeflow
 * Kubernetes
 * Machine Learning
 * MLOps
 * Model Serving
 * Python
 * Security
 * Support


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- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
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- [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing)

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