Cloud Platform Engineer

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 cloud s .   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 3 rd  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 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 ).   Experience with container deployment and management  tools (e.g. docker).   Experience with solutions for monitoring and observability. e.g.  Grafana ,  Prometheus ,  OpenSea r ch / 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 platform s.   Experience with  managing production  Kubernetes  clusters and  workloads