Cloud Platform Engineer

About this role

Responsibilities

• Develop and operate 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.
• Help to build automation to collect and analyse metrics and other 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 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.
• Work with external vendors of off-the-shelf switches, servers and storage solutions to integrate 3rd party products into our Cloud Reference Design.
• Bachelor's degree or equivalent practical experience in a relevant subject.
• 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 Linux scripting ability (bash, python, awk, sed).
• 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.

Requirements

• 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).
• Experience with container deployment and management tools (e.g. docker).
• Experience with solutions for monitoring and observability. e.g. Grafana, Prometheus, OpenSearch/ElasticSearch, Loki.
• 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.
• Experience with Openstack cloud platforms.
• Experience with managing production Kubernetes clusters and workloads.
• Programming experience with Python3 utilising classes and inheritance.

About Graphcore

How often do you get the chance to build a technology that transforms the future of humanity? Graphcore products have set the standard in made-for-AI compute hardware and software, gaining global attention and industry acclaim. Now we are developing the next generation of artificial intelligence compute with systems that will allow AI researchers to develop more advanced models, help scientists unlock exciting new discoveries, and power companies around the world as they put AI at the heart of their business. Graphcore recently joined SoftBank Group – bringing large and ongoing investment from one of the world’s leading backers of innovative AI companies. Job Summary We are looking for a Engineer to join our Cloud Platform Team and help develop and deploy services. Working closely with our colleagues in Platform Engineering, Datacentre Operations and Product Development teams, you will deploy services on our fleet of cutting-edge AI systems. As part of our Platform Engineering 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 role requiring a solid background in use of cloud infrastructure, deployment using Infrastructure-as-Code, networking and storage systems. You may have been working in an IT organisation, a datacentre, a cloud provider or as a operator of orchestration or cloud services. The Platform Engineering 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 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. Help to build automation to collect and analyse metrics and other 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 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. Work with external vendors of off-the-shelf switches, servers and storage solutions to integrate 3rd party products into our Cloud Reference Design. Skills and Experience Bachelor's degree or equivalent practical experience in a relevant subject. 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 Linux scripting ability (bash, python, awk, sed). 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 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). Experience with container deployment and management tools (e.g. docker). Experience with solutions for monitoring and observability. e.g. Grafana, Prometheus, OpenSearch/ElasticSearch, Loki. 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 with Openstack cloud platforms. Experience with managing production Kubernetes clusters and workloads. Programming experience with Python3 utilising classes and inheritance.