AI Infrastructure Engineer (Storage)
Indexed description
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
- 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
- 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.)
- 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
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search