Remote Technical Lead, GPU Infrastructure Platform

Tanqeeb; Dubai; On-site; AED 650,000 - 900,000; Full time

Benefits offered by this job

100% remote position.

Leadership and architecture ownership

Opportunity to work at scale in AI and

Job summary

Tanqeeb is seeking a Technical Lead for GPU Infrastructure with extensive hands-on experience in large-scale GPU platforms. You will architect and deliver a distributed, high-availability GPU compute platform supporting research, training, and inference workloads.

The role blends deep systems work with engineering leadership across global teams, vendors, and partners. You will drive from managed Kubernetes workloads to bare-metal GPU infrastructure, including Slurm and inference services, while

Qualifications

• 8+ years of hands-on engineering experience with at least 3 years leading infrastructure platforms.
• Extensive experience operating Slurm in production including slurmctld/slurmdbd components, partitions, QoS, accounting and upgrades.
• Proven production Kubernetes experience covering control planes, upgrades, operators, and multi-tenancy.
• Strong Linux systems expertise including kernel modules, drivers, PCIe passthrough, vfio-pci, cgroups and performance tuning.

Responsibilities

• Own the platform architecture and engineering delivery end-to-end.
• Lead and line-manage a distributed team across backend, frontend, DevOps, QA, and documentation.
• Build and operate a managed Slurm service for research and model-training workloads.
• Oversee GPU isolation and bare-metal GPU infrastructure with NVIDIA drivers and related tech.
• Define multi-tenant IaaS/PaaS for research computing with resource isolation and metering.

Skills

GPU infrastructure

Linux systems

Kubernetes

Slurm

Distributed leadership

Observability

English communication

Education

Bachelor's/Master's in CS/Engineering

Tools

NVIDIA GPUs

Prometheus/Grafana

CI/CD tooling

Job description

Tanqeeb is seeking a Technical Lead for GPU Infrastructure with extensive hands-on experience in large-scale GPU platforms. You will architect and deliver a distributed, high-availability GPU compute platform supporting research, training, and inference workloads.

The role blends deep systems work with engineering leadership across global teams, vendors, and partners. You will drive from managed Kubernetes workloads to bare-metal GPU infrastructure, including Slurm and inference services, while