Top Tech Jobs & Startup Jobs

Designs and implements cloud, bare-metal, and Kubernetes-based AI infrastructure across networking, compute, GPU, and storage. Develops scalable automation and production services, models database schemas, creates technical documentation, defines integration tests, and delivers infrastructure components into production. Requires strong experience with cloud-native architecture, Infrastructure as Code, GitOps, software development, and version control.

Design and govern the end-to-end architecture of Era4’s Kubernetes-based AI infrastructure. The role develops platform blueprints, technical standards, high- and low-level designs, multi-tenant GPU cloud architectures, capacity plans, and technology roadmaps. It coordinates Kubernetes, GPU, networking, storage, automation, security, observability, billing, and cloud services while guiding platform engineering and operations teams toward secure, scalable, reliable, and commercially viable solutions.

Design, deploy, operate, and continuously improve Kubernetes-based AI infrastructure. Responsibilities include managing Linux systems, bare-metal servers, data-centre infrastructure, NVIDIA GPU workloads, infrastructure automation, security access, platform governance, troubleshooting, documentation, customer and vendor collaboration, and on-call operational support.

Serve as the technical bridge between customers and internal teams to design, validate, and onboard AI infrastructure solutions across bare metal, BMaaS, Kubernetes and cloud-native platforms. Lead technical discovery, POCs, benchmarks, architecture reviews, reusable reference architectures, and customer workshops while influencing product roadmap and production readiness.

Design, deploy, and operate large-scale GPU-accelerated HPC and AI clusters. Manage scheduling (Slurm), networking (InfiniBand/Ethernet), provisioning, automation, monitoring, incident response, security/RBAC, and vendor engagement to ensure high availability and performance for AI workloads.

Contract Data Centre Network Engineer to design, deploy, and operate high-performance data centre networks (leaf-spine, EVPN/VXLAN), manage routing (BGP/OSPF), automate configurations (Python/Ansible/Terraform), troubleshoot network and Linux systems, support Kubernetes networking, and contribute to monitoring, documentation, and capacity planning for AI/GPU infrastructure.

The CAD Engineer will create 2D and 3D CAD drawings, collaborate with teams, and conduct site visits to gather measurements and verify conditions.