Principal Cloud Platform Engineer

What you’ll do  As Principal Cloud Platform Engineer, you’ll own the cloud foundation that Nearmap AI runs on. You’ll lead a team of up to three engineers, set the technical direction for the infrastructure layer beneath our machine learning platform, and stay hands-on in the systems you design.  This is a leadership role for a seasoned engineer who thinks in systems. Nearmap captures and processes aerial imagery at a scale that breaks most infrastructure: thousands of EKS nodes running batch inference, GPU fleets spanning two clouds, and production model endpoints behind customer products. Someone has to make that substrate reliable, secure, and affordable. That’s you.  Reporting to the Director, AI Systems Engineering, you work side by side with the Principal AI Platform Engineer. They build the machine learning platform: workflow orchestration, distributed training, serving, and LLMOps. You build what it stands on: the Kubernetes fleet across AWS and GCP, GPU-capable compute, networking, identity, infrastructure as code, CI/CD, and the observability and security foundations every AICV service depends on.  To be clear about the boundary: you own the infrastructure platform, not the machine learning tooling that runs on it, and not the customer-facing AI products. Your first customer is AICV, and it is the most demanding infrastructure customer we have. What proves out there sets the pattern for the wider Nearmap developer platform, so you’ll co-own standards, paved paths, and shared components with the Platform team in ETO.  Day to day, you’ll :  Own the technical direction for cloud infrastructure across AICV: Kubernetes fleet design on EKS and GKE, compute, networking, identity, and storage.  Design and operate GPU-capable compute — node pools, drivers, device plugins, autoscaling, and multi-tenant isolation — so the AI platform team schedules against it without thinking about the hardware.  Make the critical infrastructure design calls, and run technical evaluation and build-versus-buy with the Director and your AI platform counterpart.  Lead and mentor a team of up to three platform engineers, and own technical hiring for the team.  Write and own Terraform for the whole footprint, and build the self-service paths that let AICV teams provision what they need without raising a ticket.  Build the CI/CD and observability foundations that AICV services and the ML platform rely on: pipelines, metrics, logs, and traces.  Own reliability and cost for the infrastructure layer: service level objectives, cloud spend across AWS and GCP, capacity, and major incident response. You are on call for what you build.  Co-own the standards and paved paths of the wider Nearmap developer platform with the Platform team in ETO, so AICV patterns become company patterns.  Cloud security  Security is not a separate workstream here. It is a property of the platform…