Senior Platform Engineer - Observability

RHAELM is the sovereign AI cloud built to accelerate secure AI deployment at scale, combining power and infrastructure pipelines with global capability and local, in-country operations. Headquartered in London, with deployments across Europe and APAC, it delivers ring-fenced compute, networking, and storage infrastructure alongside a sovereign platform and flexible Bare Metal, Kubernetes, and AI-as-a-Service models. The company focuses on regulated and mission-critical sectors including Government, Defence, Healthcare, and Financial Services, providing organizations sovereign control over their AI infrastructure, platform, and data. The team is growing in Poland with a brand-new hub in Wrocław, building a local community and an observability team that develops the telemetry platform integrating layers from hardware to managed Kubernetes.

• Proven track record designing, building, and running production observability platforms at scale (e.g., LGTM stack or ELK) with metrics, log aggregation, and distributed tracing
• Deep experience with OpenTelemetry including instrumenting applications and infrastructure and building telemetry pipelines
• Experience defining SLIs/SLOs and alerting strategies
• Observability-as-code mindset: versioning and validating dashboards, alerting rules, and data sources in CI
• Solid DevOps foundation: hands-on Kubernetes, IaC in production (Terraform, Ansible), CI/CD and GitOps
• Proficient Linux knowledge for problem diagnosis
• Professional Python experience (async programming, FastAPI) for tooling, exporters, and integrations
• Ownership of architectural decisions and ability to set observability standards
• English at B2+ level or higher

Nice to have:

• Multi-tenant observability with real per-tenant isolation
• Low-level telemetry: eBPF, hardware and network devices (SNMP, syslog, gNMI, BMC), GPU accelerators, RDMA networking
• Continuous profiling
• Golang for extending OpenTelemetry Collector or writing exporters
• Advanced platform skills including self-managed Kubernetes, packaging and versioning manifests, software-defined storage
• Security fundamentals such as secrets management, PKI, mTLS, and certificate lifecycle automation
• SIEM experience with normalization, event taxonomy, index design, and capacity planning

• Building and maintaining core platform infrastructure such as managing Kubernetes clusters, CI/CD pipelines, artifact registries, and identity & secrets management systems
• Driving automation and tooling by implementing Infrastructure as Code (IaC) and streamlining operational workflows
• Developing tools for engineering and operations teams
• Ensuring reliability and security with focus on supply chain security, deployment repeatability, and production stability
• Writing code for automation, system integrations, and batch operations such as data migrations and auto-synchronizations
• Setting observability standards and owning architectural decisions across teams

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