Observability Architect

8+ years in SRE, infrastructure engineering, platform engineering, or observability-focused roles. You've operated observability infrastructure at serious scale. You know what breaks at 10x and you design for it. You have a strong bias toward simplicity. You've seen over-engineered observability stacks collapse under their own weight and you build accordingly. Deep hands-on experience with a significant subset of: Prometheus, Thanos, VictoriaMetrics, Grafana, Loki, Tempo, OpenTelemetry, ClickHouse, Elastic. Strong engineering fundamentals, proficient in Python, Go, or similar; comfortable owning complex systems end to end. Experience with Kubernetes at scale; familiarity with GPU infrastructure or HPC environments (Slurm) is a strong plus. You can architect systems, write the code, review others' work, and explain the tradeoffs clearly, all in the same week. Infrastructure-as-Code is default, not optional (Terraform, Ansible, or equivalent). You influence without authority. Teams want your opinion because it makes their work better. Preferred Experience with high-volume streaming pipelines for observability data (Kafka, Vector, Fluent Bit, etc.). Background in AI/ML infrastructure observability: GPU utilisation, training job visibility, inference latency. Prior experience defining observability strategy at an organisation level.

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