Data jobs in United Kingdom
Infrastructure Engineer (AI Platforms)
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Grs (Roadstone) Ltd
Infrastructure Engineer (AI Platforms)
Job summary
A leading tech company in the United Kingdom is seeking an Infrastructure Engineer to design and maintain platforms essential for AI workloads. This role emphasizes improving cloud infrastructure, CI/CD processes, and ensuring security for AI products. The ideal candidate has experience with AWS, GCP, or Azure, and possesses a strong security mindset. You will collaborate with various engineering teams to enhance system reliability and observability while simplifying complex infrastructures. This is a fantastic opportunity to work at the forefront of AI systems integration.
Qualifications
- Experience with AWS, GCP, or Azure and infrastructure-as-code.
- Strong understanding of CI/CD principles.
- Ability to troubleshoot production issues across layers.
Responsibilities
- Design and operate infrastructure on AWS, GCP, or Azure for AI workloads.
- Improve CI/CD pipelines and deployment strategies.
- Set up monitoring and alerting for AI components.
- Collaborate with engineers to enhance system reliability.
Skills
Tools
We are looking for an infrastructure engineer to design, build, and operate the platforms that production AI workloads depend on — from cloud infrastructure and networking to CI/CD and observability.
You will help clients create stable, secure foundations for AI systems, so that engineers can iterate quickly without compromising reliability or cost.
You will support our clients in building reliable, secure infrastructure for AI products and internal tools, working across cloud platforms, deployment pipelines, and runtime environments.
Projects might involve designing a new environment for an AI product, simplifying an overly complex platform, or improving visibility and incident response for existing services.
You will often join when a team knows their platform is "a bit of a mess" or hard to evolve, and you will help them move towards a simpler, more standardised setup that is easier to reason about, operate, and secure.
- Designing and operating infrastructure on AWS, GCP, or Azure for AI and data-heavy workloads.
- Improving CI/CD pipelines, release processes, and deployment strategies.
- Setting up monitoring, logging, and alerting for services that integrate LLMs and other AI components.
- Collaborating with application engineers to make systems more reliable, secure, and observable.
- Helping teams standardise patterns for new services so they are secure, observable, and easy to operate from day one.
- Experience with modern cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code.
- Comfortable with containers (Docker, Kubernetes or similar) and CI/CD tooling.
- Enjoys diagnosing tricky production issues across infrastructure and application layers.
- Security-conscious approach to configuration, access, and data handling, with a bias towards least privilege and defence in depth.
- Happy collaborating with both platform and application engineers to land pragmatic solutions.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.