> Markdown version of [/jobs/ext/3724406-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3724406-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Platform Engineer - **Company:** OpenKyber LLC - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Python (Programming Language), Reliability Engineering, Ansible, Prometheus, High Performance Computing, Grafana, Kubernetes, Apache Kafka, Slurm, Machine Learning Operations, Hardware Infrastructure, Vertica, Terraform, Data Pipelines - **Published:** October 14, 2026 - **Apply:** https://www.careerjet.com/jobad/usf3b1b8c2b99ea39a23c838e633173e6e ## About the Role 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.