observability engineer for AI cloud infrastructure

Verda is building a full-stack AI cloud spanning data centers, hardware, and its own cloud platform, which leading AI teams use for AI work. The company operates globally and is headquartered in Helsinki.

• Design, scale, and operate shared metrics, logs, and tracing services for infrastructure health and workload behavior
• Manage declarative Kubernetes deployments using Argo CD and GitLab and GitHub CI/CD; automate host and VM configuration using Ansible and SaltStack
• Improve monitoring for bare-metal hardware, Linux, physical and overlay networks, and Kubernetes; integrate telemetry from IPMI/Redfish, PDUs, SNMP, gNMI, and NetFlow/sFlow
• Build telemetry pipelines and dashboards for GPU clusters, AI training runs, and inference services
• Help define shared standards for OpenTelemetry instrumentation, context propagation, and Collector pipelines; support teams instrumenting Go, Node.js, and Python services and APIs
• Build dashboards and alerts, improve PagerDuty notification workflows, and participate in on-call rotations
• Work with other teams to reduce alert noise and shorten incident diagnosis and recovery
• Document standards, help teams adopt them, and evaluate and develop AI-assisted approaches to monitoring and incident investigation

• Strong hands-on experience with Grafana and production telemetry systems, including VictoriaMetrics and VictoriaLogs or comparable metrics and logging backends
• Strong Linux fundamentals, production Kubernetes experience, and experience monitoring cloud-native applications and distributed systems
• Practical experience with OpenTelemetry instrumentation, metrics, traces, structured logs, trace context propagation, and Collector pipelines
• Experience with declarative deployments, CI/CD, and configuration management using tools such as Argo CD, GitLab CI/CD, Ansible, and SaltStack
• Experience investigating production incidents, maintaining alerts, and sharing operational responsibilities within an engineering team
• Ability to explain technical decisions, guide teams, and support adoption of shared observability practices
• Будет плюсом: experience building and operating large-scale observability systems across multiple data centers; experience monitoring GPU clusters and AI/ML workloads, including NVIDIA DCGM and training or inference performance metrics; deeper experience with hardware and network telemetry, such as IPMI/Redfish, NetFlow/sFlow, SNMP, gNMI, or eBPF; experience operating across bare-metal, VM, and Kubernetes environments; experience applying LLMs, ML, or agent-based systems to automation and incident investigation; exposure to security monitoring and collaboration with SecOps teams

• Cash and equity compensation along with local benefits
• Location options: London (UK), Helsinki (Finland), or remote in EU