Top Tech Jobs & Startup Jobs in Seattle, WA

Responsible for executing core employee lifecycle processes, including onboarding, offboarding, employment changes, and leave administration, ensuring reliability and clarity in each region.

The Network Engineer will deploy and validate AI datacenter network infrastructure, manage hardware logistics, troubleshoot issues, and provide operational support while ensuring production standards.

The Talent Acquisition Lead will manage recruitment strategies, oversee a team of recruiters, and ensure quality hires for Fluidstack's business. Responsibilities include designing hiring processes, managing stakeholder relationships, and analyzing hiring metrics to improve recruitment outcomes.

The Sourcing Manager will oversee contractor labor sourcing and management for multiple site services, ensuring compliance and performance across various trades. Responsibilities include building supplier networks, negotiating contracts, and developing workforce capacity in local communities.

Own procurement for data center mechanical category (CDUs, chillers, pumps, dry coolers, piping). Negotiate multi-year supply agreements, dual-source equipment, drive qualification of second sources, and coordinate specs with manufacturing and design to meet lead times and delivery schedules.

Coordinate executive support (travel, meetings, ad-hoc requests), manage office operations (logistics, space planning, workplace technology), improve team experience (onboarding, perks, socials, onsites), lead culture initiatives across global hubs, and liaise with landlords, vendors, suppliers, and onsite candidates. Role requires full-time in-person presence.

Model and track fleet capacity (power, space, cooling, compute), forecast constraints, connect deployment schedules to sellable capacity, run scenario analyses to inform allocation and deal decisions, and build executive-ready reporting.

Build and operate large-scale GPU compute fleet tooling: metrics pipelines, alerting, Redfish/BMC telemetry, repair/RMA automation, GPU qualification, and orchestration for Kubernetes and bare-metal deployments. Own reliability, scalability, incident response, and automation to minimize manual toil.

Own and scale the GPU compute fleet: build metrics, alerting, observability, and repair automation; design GPU qualification/burn-in pipelines; own Redfish/BMC tooling and firmware telemetry; run incidents, eliminate toil, and deliver end-to-end reliability and orchestration for Kubernetes and bare-metal compute at hyperscale.

Build AI-powered internal tools and shared AI infrastructure (agents and skills), integrate LLMs with internal systems, design and ship web applications, and enable cross-functional adoption through documentation and support.