Jobs / United Kingdom / Radiant
Senior/Principal Product Manager - Cluster Platform
Radiant · 🇬🇧 London
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About the role
About our team: Radiant is redefining how AI infrastructure is built. We design and operate AI-native infrastructure platforms engineered for sovereignty, performance, and scale — powering GPU-native workloads, multi-tenant control planes, and high-performance AI systems for the most demanding environments. We are building purpose-built AI infrastructure from powered land, to compute, to software. As we scale our operations and deploy capital into the next generation of AI infrastructure, we are looking to expand our product team with leaders who can combine technical strength with execution excellence and are driven to build. Radiant was established by Brookfield, a leading global alternative asset manager with over US$1 trillion of assets under management across real estate, infrastructure, renewable power and transition, private equity and credit. Brookfield's global relationships, investment expertise and access to long-term institutional capital provide Radiant with a differentiated platform from which to develop, finance and operate AI infrastructure assets. This combination of entrepreneurial execution and institutional sponsorship enables Radiant to pursue large-scale GPU and AI infrastructure opportunities globally. Job Summary: As a Senior/Principal Product Manager - Cluster Platform, you will own the product experience and operational lifecycle for bringing new AI infrastructure clusters onto Radiant’s platform. You’ll work across cluster onboarding, acceptance, validation, benchmarking, provisioning and automation, partnering closely with infrastructure, SRE, networking, storage, platform engineering, operations, and hardware teams. This is a highly technical product role focused on making AI cluster deployment repeatable, measurable, automated, and production-ready at scale. Key Responsibilities: • Own the strategy, roadmap, and delivery for cluster onboarding, validation, acceptance, and lifecycle management. • Define the end-to-end process for taking new infrastructure from installed hardware to production-ready cluster. • Productise and automate workflows across discovery, provisioning, configuration, testing, benchmarking, acceptance, and handover. • Define cluster readiness and acceptance criteria across compute, GPUs, networking, storage, firmware, software, and reliability. • Partner with engineering to build tooling and automation for cluster deployment, validation, remediation, and lifecycle operations. • Define benchmarking frameworks for GPU performance, network fabric, storage throughput, collective communication, and workload performance. • Build clear visibility into cluster state, readiness, failures, exceptions, and deployment progress. • Identify recurring deployment friction and turn operational processes into scalable platform capabilities. • Drive prioritisation, technical requirements, delivery, adoption, and continuous improvement across the cluster lifecycle. • Define success metrics across time-to-ready, automation coverage, acceptance pass rates, deployment reliability, and cluster performance consistency. Qualifications: • Experience owning technical infrastructure, cloud platform, data centre, HPC, or AI infrastructure products. • Strong understanding of the lifecycle involved in deploying and operating large-scale compute or GPU clusters. • Strong technical fluency across: • Compute: GPU servers, bare metal, provisioning, firmware, hardware validation • Networking: high-performance fabrics, RDMA, InfiniBand/Ethernet, topology • Storage: distributed storage, throughput, latency, data paths • Orchestration: Kubernetes, Slurm, containers, schedulers • Automation: infrastructure-as-code, configuration management, workflow engines • Observability: telemetry, health checks,