At a Glance
- Tasks: Lead teams while building code and developing platforms based on Kubernetes.
- Company: This role is focused on GPU compute, not a typical cloud position.
- Benefits: Opportunity to work with cutting-edge technology in high performance compute.
- Other info: Candidates should have strong networking knowledge across clusters.
- Why this job: Join a leadership role at the frontier of GPU compute and infrastructure.
- Qualifications: Experience with bare metal infrastructure and production coding in Python or Golang.
The predicted salary is between 60000 - 80000 £ per year.
This role is a rare platform engineering leadership position building at the frontier of GPU compute. This is not a normal cloud role. We need someone who understands real infrastructure underneath the platform layer: Kubernetes, bare metal, GPU provisioning, networking, production software and operational reality of running high performance compute at scale. A lot of people have cloud and Kubernetes experience. Far fewer have true bare metal experience. That is the point we need to understand properly. This will suit someone from GPU cloud, AI infrastructure, HPC, managed Kubernetes, bare metal cloud, hyperscale infrastructure or deep platform engineering environments.
Responsibilities
- Lead teams while still building code.
- Write production grade code.
- Develop platforms based on Kubernetes.
- Work closely with bare metal infrastructure.
- Provision GPU or deploy workloads across GPU environments.
- Discuss networking, clusters, and how the platform actually runs.
Key Experience
- Kubernetes platform engineering.
- Bare metal cloud or bare metal infrastructure.
- GPU provisioning or GPU deployment.
- Strong networking knowledge across clusters.
- Production grade coding in Python and Golang or Rust.
- Linux and distributed systems experience.
- Experience leading technical work or mentoring strong engineers.
- Bare metal experience (essential).
Team Lead, Platform Engineering employer: We Love Alfa
This position is located in a dynamic environment focused on GPU compute. The team values deep platform engineering expertise and offers opportunities to work with advanced technologies. Join a group that prioritises innovation in high performance computing.
