Site Reliability Engineer
Verda is a Helsinki-headquartered full-stack AI cloud provider offering on-demand GPU compute, clusters, serverless containers, storage, APIs, and related AI infrastructure.
Funding history
About Verda
Formerly DataCrunch, Verda operates European AI cloud infrastructure for the full AI lifecycle, from prototyping and distributed model training to scalable inference. It manages data-center infrastructure, hardware, cloud-platform services, and an in-house AI Lab.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will keep Verda's GPU cloud running and make it more reliable every quarter. You start with well-scoped work alongside senior SREs and grow into owning parts of the platform from build to production. You work hands-on across deployments, Kubernetes platforms, secrets, observability and tooling that connects bare-metal GPU servers to customer-facing services. Once ready, you join a paid primary/secondary on-call rotation, paired with experienced engineers.
Requirements
- 3+ years in SRE, infrastructure, platform or systems engineering, or equivalent hands-on experience from internships
- Solid Linux fundamentals and troubleshooting experience
- Hands-on Kubernetes experience, ideally in production
- Some experience with infrastructure automation or GitOps and observability tools
- Experience writing tooling and automation in Go or Python
- Solid networking fundamentals: TCP/IP, DNS and load balancing
- Clear communication and ability to work across teams
Responsibilities
- Run and improve services that keep data centers operating, from deployment pipelines to secret provisioning
- Contribute to SLIs and SLOs for core platform services
- Take part in on-call, respond to incidents and contribute to blameless reviews
- Diagnose failures across the stack from GPU and server hardware through Linux and networking to Kubernetes
- Build automation that removes repetitive operational work, including AI-assisted and agent-based tooling
- Make deployments safer with release criteria, readiness checks, progressive rollouts and fast rollback
- Extend observability with metrics, logs, traces and alerts
- Contribute to capacity planning, failover and redundancy design for a growing GPU fleet
- Raise reliability risks early and log them in the infrastructure risk register
- Write runbooks and documentation and help peers through code reviews
Benefits
- Cash and equity compensation
- Local benefits
- Paid on-call rotation