FluidStack

2 weeks ago

Production Engineer, IaaS

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Build and operate the observability and control-plane infrastructure that makes large-scale AI compute fleets legible and manageable. Own production data pipelines, correlation/decoration engines, health checks, and a versioned API surface used across the company. Design unified machine management, distributed command execution, and fleet state “source of truth,” including onboarding new hardware through ZTP, DHCP, DNS, and IaaS.

Location: San Francisco, New York, Austin, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own the observability platform, building and operating data pipelines, decoration/correlation, and healthcheck frameworks from site to device and link.
•Define and build the API surface for infrastructure by designing contracts between production infrastructure and the tools that operate the hyperscale fleet.
•Build the production control plane, including unified machine management, state inspection, and distributed command execution with Kubernetes-based infrastructure.
•Own fleet state as the source of truth, covering SLOs, site lifecycle state, and integrations so system reality matches what the platform reports.
•Land new hardware into the platform via ZTP, DHCP, DNS, and artifacts, ensuring each new XPU generation and site integration goes through IaaS before production.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Perks:RetirementHealth InsuranceDentalVisionPaid Leave

Key Requirements

•Treat toil as a bug by automating repeat manual work and building solutions that remove human effort.
•Design APIs that age well and avoid leaky abstractions at scale by learning from production pain points.
•Comfortable moving toward ambiguity—build the map in unclear domains and explain it to others.
•Learn quickly in unfamiliar domains and reach real competence fast.
•Experience shipping production services other teams depend on at scale, and familiarity with AI tooling (LLM APIs, MCP servers, agentic frameworks).

Experience:AI infrastructureDistributed systemsData pipeline engineering

Skills:Extreme ownershipVelocityFirst principlesIncident responseAbility to learn quickly

Tech Stack:KubernetesPrometheusThanosVictoriaMetricsTemporalCadenceBMCRedfishGoPythonPostgresLLM APIsMCP serversAgentic frameworksClaude CodeCursorZTPDHCPDNSIaaS

Company Brief

FluidStack

Builds and deploys large-scale GPU cloud infrastructure for AI labs, enterprises and governments, providing high-performance AI training and inference capacity and rapid data-center deployment services.

Industry: Cloud Computing

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: New York, United States

Founded: 2017

Glassdoor: 4.7

Website LinkedIn Glassdoor

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FluidStack

2 weeks ago

Production Engineer, IaaS

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Austin, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own the observability platform, building and operating data pipelines, decoration/correlation, and healthcheck frameworks from site to device and link.
•Define and build the API surface for infrastructure by designing contracts between production infrastructure and the tools that operate the hyperscale fleet.
•Build the production control plane, including unified machine management, state inspection, and distributed command execution with Kubernetes-based infrastructure.
•Own fleet state as the source of truth, covering SLOs, site lifecycle state, and integrations so system reality matches what the platform reports.
•Land new hardware into the platform via ZTP, DHCP, DNS, and artifacts, ensuring each new XPU generation and site integration goes through IaaS before production.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Perks:RetirementHealth InsuranceDentalVisionPaid Leave

Key Requirements

•Treat toil as a bug by automating repeat manual work and building solutions that remove human effort.
•Design APIs that age well and avoid leaky abstractions at scale by learning from production pain points.
•Comfortable moving toward ambiguity—build the map in unclear domains and explain it to others.
•Learn quickly in unfamiliar domains and reach real competence fast.
•Experience shipping production services other teams depend on at scale, and familiarity with AI tooling (LLM APIs, MCP servers, agentic frameworks).

Experience:AI infrastructureDistributed systemsData pipeline engineering

Skills:Extreme ownershipVelocityFirst principlesIncident responseAbility to learn quickly

Tech Stack:KubernetesPrometheusThanosVictoriaMetricsTemporalCadenceBMCRedfishGoPythonPostgresLLM APIsMCP serversAgentic frameworksClaude CodeCursorZTPDHCPDNSIaaS

Company Brief

FluidStack

Industry: Cloud Computing

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: New York, United States

Founded: 2017

Glassdoor: 4.7

Website LinkedIn Glassdoor