> Markdown version of [/jobs/ext/4128958-infrastructure-engineer-cloud](https://www.wearedevelopers.com/jobs/ext/4128958-infrastructure-engineer-cloud). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure Engineer, Cloud - **Company:** LEGO Digital Play - **Location:** London, United Kingdom - **Salary:** £57,741 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Cloud Computing, Continuous Integration, Data as a Services, Identity and Access Management, Prometheus, Azure Machine Learning, Software Engineering, Google Cloud, Grafana, Information Technology, Machine Learning Operations, Cloudwatch, Terraform, OpenSearch - **Published:** October 31, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5947727459 ## About the Role * Bachelor's or higher degree in Computer Science, Software Engineering or a STEM field, or equivalent practical experience. * Deep hands-on expertise in AWS, operating production workloads across multi-account environments, networking, IAM, managed data services and containerisation. * Strong experience with Terraform at scale, including module design, state management and CI/CD-driven infrastructure workflows. * Demonstrated ability to build infrastructure from a low or zero baseline, comfortable with greenfield work, ambiguity and revisiting early decisions quickly. * Hands-on experience designing and operating reliability and observability systems, covering SLO design, structured incident practices, and metrics, tracing and log aggregation, with tools such as CloudWatch, Grafana, Prometheus or OpenSearch. * Security- and privacy-minded, designing for data protection and regulated consumer environments at the infrastructure layer, with awareness of GDPR and COPPA. * Fluency with modern AI tooling in development and operations, using it to move faster while retaining the judgement to catch its failures and stand behind the quality of what ships. * Clear communicator with technical and non-technical audiences, able to explain trade-offs and report progress in a structured way., * Production experience with Google Cloud alongside AWS. * Experience in AI/ML infrastructure, including GPU orchestration, model serving (Triton, vLLM or equivalent) and MLOps tooling. * Experience contributing to an internal developer platform or paved-road system. * Background in games or interactive-media infrastructure, including content and asset pipelines. * Experience in brand-safe or regulated consumer ecosystems such as children's products, health or fintech. ## Description As Infrastructure Engineer, Cloud, you will build and operate the cloud foundation that LEGO Digital Play's engineering teams and internal studios ship on. You will own the landing zones, infrastructure as code, observability and security controls that make that foundation reliable, secure and child-safe by default, partnering with AI, engineering, security and studio teams to turn platform standards into paved roads. This is a newly created individual contributor role based in London, England, reporting to the Director of Technical Operations. Key Responsibilities * Build and operate the cloud foundation, AWS-first and extending to Google Cloud where needed, covering landing zones, account and project structure, networking and secrets management, so that engineering teams and studios build on a consistent, secure base. * Embed security, privacy and compliance controls into the cloud foundation by default, including least-privilege IAM, encryption at rest and in transit, audit logging, and GDPR and COPPA requirements at the infrastructure layer. * Own infrastructure as code in Terraform, establishing reusable modules, standards and review practices the wider team can build on. * Build paved roads and self-service tooling that let engineering teams and internal studios ship reliably and quickly without reinventing the basics. * Establish reliability and observability across the platform, including SLO instrumentation, metrics, tracing, log aggregation and the conventions that live-service and product teams depend on. * Partner with the AI teams to deliver AI/ML platform infrastructure, including GPU orchestration, model serving infrastructure and inference APIs. * Instrument cost visibility and drive FinOps practice, helping build a cost-aware engineering culture from the foundation up. * Shape architectural decisions and technical standards as an early member of a new infrastructure team, iterating at speed in a greenfield environment.