AI INFRASTRUCTURE& NEOCLOUDEXECUTIVE SEARCH

Talent working at the compute layer across large-scale GPU fleets, accelerated computing environments and high-performance computing infrastructure.

GPU compute, HPC, accelerated computing, GPU clusters, bare-metal infrastructure, performance engineering.

Modern AI clusters depend on exceptionally high-throughput, low-latency networking. Sentiro identifies engineers designing and operating the fabrics connecting increasingly large GPU environments.

InfiniBand, Ethernet, RDMA, RoCE, NCCL, NVIDIA BlueField, Spectrum-X, GPU fabrics.

The software infrastructure required to turn large-scale GPU compute into reliable, usable capacity.

Kubernetes, Slurm, Linux, Terraform, containers, scheduling, workload orchestration, control planes.

At GPU scale, reliability becomes a core engineering discipline. Small failures can strand expensive compute capacity, making fleet health, telemetry, observability and remediation commercially critical.

GPU fleet reliability, cluster reliability, SRE, production engineering, failure detection, remediation, observability, telemetry.

Serving increasingly large models reliably and economically has created a distinct engineering discipline spanning inference systems, model serving, runtime engineering and performance optimisation.

AI inference infrastructure, inference engineering, model serving, ML infrastructure, distributed inference, GPU kernels, GPU runtimes.

AI infrastructure extends beyond software. Increasing compute density requires specialist leadership and engineering across hardware deployment, data-centre systems, capacity and physical infrastructure.

AI data centres, GPU servers, physical infrastructure, capacity, hardware deployment, AI factories.

AI infrastructure companies increasingly need engineers capable of operating between the underlying platform and technically sophisticated customers. These individuals combine strong systems knowledge with the ability to diagnose, integrate and deploy complex AI infrastructure in production environments.

Forward Deployed Engineers, Solutions Engineers, Customer Engineers, deployment, integration.