Platform Engineer: Observability & Fleet Control

Fluidstack; Seattle (WA); On-site; USD 175,000 - 300,000; Full time

Benefits offered by this job

Stock options

Health/dental/vision insurance

Generous PTO

Job summary

Fluidstack is seeking a highly capable engineer to own the observability platform, build data pipelines, and define the API surface for our hyperscale infrastructure. You will design and operate a Kubernetes-based production control plane, ensure fleet state accuracy, and onboard new hardware through IaaS processes.

You should be comfortable with AI tooling, distributed systems, and creating scalable interfaces that other teams rely on.

Qualifications

• You treat toil as a bug and automate repeatable tasks.
• You design APIs that age well and avoid leaky abstractions.
• You embrace ambiguity, map the domain, and communicate clearly to others.
• You learn quickly and gain competence in unfamiliar domains.
• You carry a pager, run incidents, and fix root causes.
• You are fluent with AI tooling and AI coding assistants.
• You have shipped production services used by other teams at scale.
• Bonus: distributed systems and data pipeline engineering, time-series stacks, API versioning, workflows.

Responsibilities

• Own the observability platform: build data pipelines, decoration/correlation engine, and health-check framework.
• Define and build the API surface for infrastructure and tooling.
• Build production control plane and Kubernetes-based infrastructure.
• Own fleet state as source of truth, maintain SLOs and lifecycle state.
• Land new hardware into the platform via IaaS processes (ZTP, DHCP, DNS, artifacts).

Skills

APIs design

Distributed systems

Data pipelines

Go

Python

PostgreSQL

AI tooling

Tools

Temporal

Cadence

Prometheus

VictoriaMetrics

Redfish

Go

Python

PostgreSQL

Job description

Fluidstack is seeking a highly capable engineer to own the observability platform, build data pipelines, and define the API surface for our hyperscale infrastructure. You will design and operate a Kubernetes-based production control plane, ensure fleet state accuracy, and onboard new hardware through IaaS processes.

You should be comfortable with AI tooling, distributed systems, and creating scalable interfaces that other teams rely on.