Senior Cloud Engineer (Fixed Term)

Fixed-term: The funds for this post are available for 2 years in the first instance. 

We are looking for an experienced and enthusiastic Senior Cloud Engineer to be part of a new and exciting initiative to develop the UK Regional Centre (UKSRC) for the Square Kilometre Array, the world's largest radio telescope.

The role is based in Research Computing Services (RCS) a leading UK National Supercomputing Centre and home to Dawn, the fastest AI supercomputer in the UK, providing facilities and services to world-renowned scientists, clinicians and engineers across the UK and Europe.

The University of Cambridge RCS provides HPC resources for UKSRC and is developing novel federated cloud platform technologies as well as providing leadership on system architecture. 

The successful candidate will become part of a diverse team of systems engineers, astronomers, and computer scientists developing advanced solutions to support world class science and deliver service for processing data from the world's largest radio telescope.

You'll be working in a team of Cloud engineers, in collaboration with National and International colleagues to help deliver, operate and support the UKSRC and international cloud infrastructure and HPC resources. 

Responsibilities 

• Design, deploy, and manage OpenStack-based cloud environments.
• Troubleshoot and resolve complex issues related to cloud infrastructure and HPC environments.
• Stay current with industry trends and emerging technologies to propose innovative solutions.
• Support Science teams by providing them with technical expertise and advice on best practices for using cloud-based environments. 

Skills and experience

Preferred: 

• Deployment and administration of Linux operating systems.
• Utilizing Ansible for configuration management.
• Strong understanding of virtualization technologies and cloud architecture.
• Experience with scripting languages (Python, Bash, etc.) for automation.
• Knowledge of containerization technologies (Docker, Kubernetes).
• Solid understanding of networking principles in cloud environments. 

Desirable: 

• Experience in working in a scientific environment and/or providing support to researchers.
• Experience working with HPC clusters and parallel file systems.
• Knowledge of GPU-accelerated computing and associated frameworks.
• Experience Performance profiling, monitoring tools, and software performance optimization.

More information about the role is attached in the 'Further Particulars' document.

The University is supportive of hybrid working and we aim to enable as many staff as possible work in a hybrid way if they wish and where their role allows. This role allows the post holder to be office based, work in a hybrid way or remotely with only minimal office attendance.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a security check.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

We particularly welcome applications from women and /or candidates from a BME background for this vacancy as they are currently under-represented at this level in our department.

To apply online for this vacancy and to view further information about the role, please click on the apply button above. 

All queries should be directed to recruitment@uis.cam.ac.uk in the first instance. 

Please quote reference VC42390 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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