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Manage day-to-day GRC program across SOC 2, ISO 27001, NIST 800-53 and FedRAMP equivalency: evidence collection, control monitoring, audit readiness, policy ownership, recurring control operations, POA&M management, and onboarding new sites into the compliance program.

The Business Process Controls Lead will design and improve core business processes, enhance operational efficiencies, and collaborate with cross-functional teams to support growth.

The Program Manager for Deployments will lead large-scale AI infrastructure projects, coordinating between teams, managing deployments, and maintaining project documentation.

Serve as the on-site Tier 3 escalation for network and structured-cabling incidents in a data center. Troubleshoot and resolve physical-layer faults, validate repairs, own cabling and fiber infrastructure, interpret device diagnostics, escalate and document issues, and act as the sole on-site network/ICT resource partnering with Network Operations.

The Site Project Manager oversees project delivery at Fluidstack's data centers, managing all aspects of site projects from scope to budget while ensuring minimal disruption to operations.

Lead and scale talent acquisition for Fluidstack's Data Center organization: own hiring strategy, execute critical searches, build and manage a TA team, partner with senior hiring managers on workforce planning, design fast high-quality hiring processes, and own recruiting metrics and infrastructure.

Own hiring strategy and execution for the Software organization and scale TA across manufacturing, supply chain, and operations. Build and lead a team of recruiters, sourcers, and coordinators; partner with senior hiring managers on forecasting and mapping talent needs; design hiring processes, ATS workflows, interview rubrics, and metrics; run critical searches (including hard-to-fill skilled trades and procurement roles); and drive employer brand and recruiting performance.

Build and operate the observability platform, data pipelines, and production control plane for a hyperscale GPU fleet. Define infrastructure API surfaces, ensure fleet state is source of truth, integrate new hardware (ZTP/DHCP/DNS), and maintain Kubernetes-based infrastructure and SLOs. Own incidents, postmortems, and system reliability.

Design end-to-end datacenter network architectures for AI training and inference: topology, IP/routing, RDMA/lossless fabrics, physical integration (rack, power, cabling), and comprehensive HLD/LLD documentation. Collaborate with hardware, operations, cabling, software, and validation teams to produce deployable, scalable, and performance-validated designs.

Design, build, and operate the observability and control-plane for a hyperscale GPU fleet. Own data pipelines, API surface, fleet state as source-of-truth, distributed command execution, and clean hardware/site onboarding (ZTP/DHCP/DNS). Ensure production reliability, run incidents, and drive automation to eliminate toil.