Software Engineer, Facilities
Fluidstack · Austin, TX
About this role
## About Fluidstack We exist to make humanity more free. Powerful AI will be the biggest lever for human choice—but only if models are aligned with what humanity actually wants. Fluidstack builds and operates **civilization-scale AI compute infrastructure**, delivering **10 to 100s of GW** faster than anyone else by rethinking every layer of the stack. ## The Facility Controls Team You’ll help build the production services that enable real-time control and reliable data flow across sites, including: - **Controlling datacenter power demand** in real time while staying within equipment operating limits - **Integrating power, cooling, and on-site generation** so they can be monitored and controlled together - **Automating commissioning tests** to verify equipment behavior and record results - **Automating software deployment/configuration** as new sites and equipment come online - **Processing facility telemetry** and serving current + historical data through reliable APIs You’ll build services such as **telemetry pipelines, equipment models, control APIs, and test orchestration**. **Tech you may work with:** Go, NATS, ClickHouse, Redis, Protobuf/gRPC, Kubernetes. ## Role Scope - **Build and own services** other teams depend on (device integrations, telemetry pipelines, equipment models, and APIs across sites) - **Design the messaging + state layer**: preserve ordering where needed, handle lagging consumers, and recover after restarts without losing data or applying actions twice - **Own data contracts and engineering standards**: make identity/units/timestamps/data quality explicit; evolve schemas/APIs without breaking consumers - **Implement the path from control request → confirmed result**: authorization, deadlines, equipment constraints, safe retries - **Build observability** that explains failures (ingestion lag, dropped data, stale readings, query latency, command completion) - **Prove behavior across the whole system** using unit/integration tests and simulated devices ## What We’re Looking For - Experience building **large-scale software systems** that produce/process high volumes of data - Shipped production code in **Go, Python, or TypeScript** (and can pick up the language the problem demands) - Worked with **high-throughput messaging** (NATS or Kafka), understanding ordering, delivery guarantees, backpressure, and concurrency vs. correctness - Designed data models for **time-stamped data at scale**; can reason about write throughput, query performance, retention, and schema evolution - Instrumented production services with **metrics/logs/profiling** and used it to diagnose bottlenecks/incidents - Designs before building: can explain alternatives, tradeoffs, and iteration when requirements change - Defines interfaces/failure boundaries deliberately; tests include unavailable-dependency and recovery paths - Can trace data from source through services/storage; handles missing/duplicate/late/invalid data and treats stale vs. wrong values differently ### Bonus - Prior **datacenter or controls** experience ## Useful Experience (Stack) - Go, NATS, Redis, ClickHouse, Protobuf/gRPC, Kubernetes, ArgoCD - Prometheus + Grafana - Industrial protocols such as **Modbus** or **OPC UA** ## How We Operate - **Be a barrel**: full autonomy, own scope end-to-end, no permission required to operate outside your core role - **Insane urgency**: move fast - **Reason from first principles**: challenge assumptions; best idea wins - **Love of the
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