Senior Cloud Engineer (K8S)

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary We are looking for a Senior Engineer to join our Cloud Platform Team and help develop and deploy clouds and services . Working closely with our colleagues in Software Platform, Datacentre Operations and Product Development teams, you will deploy services on our fleet of cutting-edge AI systems. As part of our Software Platform organisation, you will be involved in the cloud integration, validation, performance benchmarking, optimisation, and development of our high-performance AI solutions . These include in-house AI systems alongside off-the-shelf high-performance servers, switches and storage solutions . This is a hand-on technical role requiring a solid background in the use of cloud infrastructure, deployment using Infrastructure-as-Code, observability, high-performance networking and storage systems . You may have been working in an IT organisation, a datacentre, a cloud provider or as a developer of orchestration or cloud services . The Software Platform team at Graphcore We build Graphcore products into large-scale AI solutions for our customers and the Cloud Platform Team is responsible for providing such systems to both internal users via private clouds and customers via our own public clouds . Often the internal systems will be using and developing pre-release hardware and software , so it’s vital you are comfortable with unproven components. Responsibilities and Duties Develop and operate Kubernetes-managed end-user services on our private clouds and support internal users in their use. You will turn end-user and product requirements into deployed services. Work with our Datacentre Operations Engineers to maintain and operate the fleet of AI systems at peak performance in our private clouds. Configure and test new Graphcore AI hardware and systems using Continuous Deployment and Infrastructure-as-code in internal and external datacentres. Skills and Experience (all required) Bachelor's degree or equivalent practical experience in a relevant subject. Experience with managing production Kubernetes clusters and workloads with a continuous delivery tool such as ArgoCD . Solid software engineering or IT experience with a proven track record of delivering technical output as an individual contributor. Experience working in an AGILE and SCRUM framework , including understanding of priorities, risks, issues, impacts and constraints . Strong proven L inux scripting ability (bash, python, awk, sed ). Strong proven Linux system administration ( U buntu, RHEL and variants). Experience with a version control system (preferably G it ) and using it to manage system configuration or automation. Experience with Continuous Integration or testing pipelines using GitLab, GitHub or similar. A solid hands-on understanding of the technologies underpinning cloud services ( APIs, virtualisation of CPUs, IO, systems), virtual networks, block storage, resource management and monitoring. Experience with IAC automation tools ( Terraform/ OpenTofu , Ansible , Packer ). Good communication and presentation skills , and experience dealing with end-users of IT services. An ability to work independently on critical infrastructure with minimal oversight , and with a focus on end-user availability . Desirable but not required: Experience