Staff+ Software Engineer - Cloud Availability Platform Engineering (Observability)

Staff+ Software Engineer - Cloud Availability Platform Engineering (Observability) Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role: We are looking for a Staff Software Engineer to lead the architecture and evolution of Crusoe’s observability platform at scale. In this role, you will define and drive the strategy for how telemetry is collected, processed, and leveraged across Crusoe’s global cloud infrastructure. You will architect and operate a highly scalable observability platform that powers reliability, performance insights, and operational excellence across Crusoe’s AI-optimized cloud. Your work will enable engineers to deeply understand the behavior of complex distributed systems through metrics, logs, and traces while ensuring the observability platform itself remains reliable, efficient, and scalable. As a Staff engineer, you will operate as a technical leader across organizations — shaping Crusoe’s observability roadmap, influencing platform architecture, and partnering closely with infrastructure, AI platform, and product teams to embed observability best practices across the company. What You’ll Be Working On: - Leading the architecture and long-term strategy for Crusoe’s observability platform supporting multi-region, multi-datacenter Kubernetes infrastructure - Designing and operating large-scale telemetry systems (metrics, logs, traces) capable of supporting high-volume AI/ML, GPU, and distributed workloads - Architecting end-to-end telemetry pipelines, including ingestion, storage, indexing, querying, and visualization layers - Driving adoption and evolution of Crusoe’s monitoring ecosystem, including Prometheus, Alertmanager, Thanos/Cortex/Mimir, Grafana, and OpenTelemetry - Designing highly scalable log ingestion and processing pipelines using technologies such as Fluent Bit, Vector, Loki, or ELK/OpenSearch - Building and evolving distributed tracing platforms (Tempo, Jaeger, OpenTelemetry) integrated with service meshes, APIs, and networking layers - Establishing observability standards across the organization, including SLIs, SLOs, error budgets, and instrumentation best practices - Driving reliability and cost efficiency improvements across telemetry pipelines operating at massive scale - Automating provisioning and lifecycle management of observability infrastructure using Kubernetes, Terraform, and internal tooling (Go, Python) - Embedding security and multi-tenancy into the observability platform, including RBAC, TLS, secrets management, and tenant isolation - Partnering with platform and product engineering teams to integrate observability into services, infrastructure, and development workflows - Mentoring engineers and providing technical leadership across the Cloud Availability organization - Influencing platform architecture decisions and shaping the long-te ... (truncated, view full listing at source)