AI Infrastructure Engineer (Storage)

We support technology-focused start ups, each with unique data management challenges, and are seeking an experienced Infrastructure Engineer to help them design, deploy and maintain high-performance storage systems for their AI and data-driven workloads. The successful candidate will combine deep experience architecting and managing distributed, cloud, and tiered storage solutions with strong Linux and automation skills.

In this role you will:

• Design, implement, and maintain storage platforms that support large-scale AI and data pipelines
• Manage distributed storage systems such as Ceph, Lustre, or BeeGFS.
• Oversee tiered storage architectures, optimising data movement across high-performance, object, and archival tiers.
• Ensure data integrity, availability, and security across on-premises and cloud environments.
• Develop automation and monitoring tools using Bash, Python, or similar scripting languages.
• Manage and secure container images and related storage used for AI and ML workloads.
• Integrate storage systems with public cloud services (AWS, Azure, GCP) and hybrid environments.
• Troubleshoot complex storage and data flow issues, collaborating closely with AI platform and infrastructure teams.
• Contribute to ongoing architecture improvements, performance tuning, and capacity planning.

Requirements

To be considered candidates should meet most of the following requirements:

• Strong Linux system administration background.
• Proven experience installing, configuring, and maintaining Ceph clusters or similar technologies in a production environment.
• Familiarity with distributed filesystems (e.g., Lustre, BeeGFS) and cloud-based storage services (e.g. EC2).
• Experience with tiered storage management and lifecycle data policies.
• Scripting and automation proficiency (e.g. Bash, Python, Terraform/OpenTofu, Ansible).
• Understanding of data security best practices and compliance considerations.
• Experience working with container technologies (e.g. Docker, Kubernetes) and image storage registries.
• Strong analytical, troubleshooting, communication and documentation skills.

We also value:

• Knowledge of GPU compute environments or AI training infrastructure.
• Experience with monitoring and observability tools (Prometheus, Grafana, etc.).
• Contributions to open-source storage, data management, or infrastructure projects.
• Familiarity with object storage systems (S3, RADOS Gateway, MinIO, etc.).

Benefits

• A collaborative and supportive work environment.
• The opportunity to have a high impact in a growing organisation.
• Competitive salary package and pension.
• Professional development opportunities.
• Networking opportunities with influential people from across the tech sector and academia.
• A vibrant office environment located a few minutes walk away from Cambridge train station.