Cloud Engineer

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 Soft Bank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing Soft Bank 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.

We are looking for an experienced Staff Engineer to join our Cloud Platform Team and help develop and deploy clouds and services. Working closely with our colleagues in Software Platform, Data centre 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 hands‑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 data centre, a cloud provider or as a developer of orchestration or cloud services.

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 cloud. Often the internal systems will be using and developing pre‑release hardware and software, so it’s vital you are comfortable with unproven components.

• Operate and extend existing Open Stack‑based cloud services and contribute to the deployment and development of new ones.
• Develop and operate end‑user services on our clouds and support internal users in their use. You will turn end‑user and product requirements into deployed services.
• Help to build automation to collect and analyse metrics and other observability data from the cloud services to support clear identification and reporting of any issues. Work with users to provide information of any product‑related issues to Engineering and QA departments.
• Work with our Data centre 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 data centres.
• Drive corrective actions for systems that are not operating correctly, working with DC operations and Graphcore Engineering as required.
• Work with external vendors of off‑the‑shelf switches, servers and storage solutions to specify, benchmark and integrate third‑party products into our Cloud Reference Design.

• Bachelor’s degree or equivalent practical experience in a relevant subject.
• Solid infrastructure or IT experience with a proven track record of delivering technical output as an individual contributor.
• Experience managing or operating on‑premises or private‑cloud environments.
• Experience specifying, scoping, estimating and detailing work plans in an AGILE and SCRUM framework, including priorities, risks, issues, impacts and constraints.
• Strong proven Linux scripting ability (bash and python required).
• Strong proven Linux system administration (Ubuntu, RHEL and variants).
• Experience with a version control system (preferably Git) and using it to manage system configuration or automation.
• Experience with Continuous Integration or testing pipelines using Git Lab, Git Hub or similar.
• Hands‑on experience deploying services into public or private clouds using…