> Markdown version of [/jobs/ext/2051117-infrastructure-engineer](https://www.wearedevelopers.com/jobs/ext/2051117-infrastructure-engineer). 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 - **Company:** The Wave - **Location:** Cambridge, UK - **Salary:** £50,273.0 - **Contract:** Permanent contract - **Skills:** Computing Platforms, Cloud Engineering, Data Infrastructure, Software Debugging, Linux, Job Scheduling, Role-Based Access Control, Digitalocean, Scientific Computating, Sysadmin, Kubernetes, Bare Metal, Slurm, Terraform - **Published:** August 14, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5841126579 ## About the Role * Experience running Kubernetes in production, ideally including bare metal. * Cloud-native mindset: you think in Kubernetes and treat on-prem machines as just another part of the cluster. * Some Linux sysadmin experience, to manage our bare metal boxes. * Comfortable with compute-heavy, batch-style workloads. * Experience with Infrastructure as Code (Terraform) * Willingness to take ownership and make pragmatic calls. * Being able to architecture robust/reliable systems, Care about the experience of the people relying on your infrastructure. Nice to have / Beneficial * HPC-style job scheduling (Kueue, Slurm, MPI, or similar). * Experience with large scientific or array datasets. * Any background in photonics, semiconductors, EDA, or scientific computing. We are particularly interested in people who can solve complex problems, learn quickly and make a meaningful contribution. If you do not meet every requirement but believe you could be successful in the role, we would still encourage you to apply. ## Description * The compute platform - Kubernetes across on-prem and cloud, run as one coherent system, including cloud bursting. Making it easy for the team to submit, monitor and debug compute-heavy jobs without needing to understand the machinery underneath. * Observability - Monitoring and alerting that tells you something is wrong before a user does. * Data infrastructure - Reliable, well-organised storage and access for large scientific datasets, with backups you can trust. * Security - Making sure our environment is secure (RBAC, secrets, policies, zero trust networking) Our core stack Kubernetes, cloud (DigitalOcean/GCP) alongside bare metal, Terraform. Both CPU and GPU workloads. We want to build things once, so they don't demand constant attention: it requires a lot of automation, monitoring relevant metrics, and designing robust systems. If your instinct on seeing a recurring manual task is to engineer it out of existence, you will fit in well here. It is a broad role with a lot of autonomy, so you will set the standards and we will trust you to run with them. 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