Product Manager, Managed Services

ABOUT FLUIDSTACK At Fluidstack, we build the compute, data centers, and power that will fuel artificial superintelligence. We work with Anthropic, Google, Meta, AMI Labs, and Black Forest Labs to deploy gigawatts of compute at industry defining speeds. We are investing tens of billions of dollars in US infrastructure. In 2026, we will deploy 1GW. In 2027, 10GW. Our team is small, fast, and obsessed with quality. We own outcomes end-to-end, challenge assumptions, and treat our customers' problems as our own. No task is beneath anyone here. There are a few thousand people who will shape the trajectory of superinteligence. Come and be one of them. ABOUT THE ROLE We're hiring a Product Manager to own our managed services portfolio, including SLURM and Kubernetes control planes. You'll define the product vision and roadmap for how enterprises deploy, manage, and scale workloads on Fluidstack's infrastructure—from initial cluster provisioning through lifecycle management, observability, and optimization. This role sits at the intersection of infrastructure, developer experience, and operational excellence, working closely with engineering, datacenter operations, and customer-facing teams to build control plane capabilities that scale to 100k+ GPU megaclusters. WHAT YOU'LL DO - Own the product roadmap for managed SLURM and Kubernetes offerings, including control plane architecture, autoscaling, multi-tenancy, and cluster lifecycle management - Define requirements for control plane performance, reliability, and availability—including API rate limits, etcd scaling, provisioning tiers, and failure recovery mechanisms - Work with engineering to design automated provisioning workflows, health monitoring systems, and node lifecycle controllers that minimize cluster downtime and maximize GPU utilization - Partner with datacenter and networking teams to ensure control plane infrastructure scales seamlessly across geographic regions and supports hybrid deployment models - Drive decisions on when to build vs. integrate with ecosystem tools (Rancher, OpenShift, Slurm accounting, workload orchestrators) based on customer requirements and competitive positioning - Define metrics and SLAs for control plane uptime, API performance, scheduler throughput, and pod/job launch latency - Conduct customer discovery to understand pain points around cluster management, job queueing, resource allocation, and multi-cluster orchestration - Create product documentation, deployment guides, and reference architectures for enterprise customers running large-scale AI training and inference workloads - Analyze competitive offerings from AWS EKS, Google GKE, DigitalOcean DOKS, and specialized HPC providers to inform feature prioritization and pricing strategy ABOUT YOU - 5+ years product management experience with at least 3 years focused on infrastructure, platform, or cloud services - Deep technical understanding of Kubernetes control plane architecture (kube-apiserver, etcd, scheduler, controller-manager) and SLURM job scheduling - Experience building or managing infrastructure products that serve technical users (platform engineers, ML engineers, researchers) - Track record of shipping features that improved cluster reliability, reduced time-to-deployment, or increased resource efficiency at scale - Strong grasp of distributed systems concepts: consensus protocols, failure modes, backpressure handling, and operational complexity tradeoffs - Familiarity with GPU workload patterns (multi-node training, inference serving, batch processing) and how control plane design affects performance - Ability to synthesize customer feedback, operational data, and competitive intelligence into clear product requirements and technical specifications - Experience working with engineering teams to debug production incidents, analyze root causes, and translate findings into product improvements - Comfortable navigating ambiguity and making pragmatic tradeoffs between feature completeness, time-to-market, and technical debt - Bonus: Experience with HPC schedulers (LSF, PBS, Grid Engine), cloud-native storage (Ceph, Lustre), or datacenter automation COMPENSATION To provide greater transparency to candidates, we share base pay ranges for all US-based job postings. Our compensation package includes base salary, equity, benefits, and for applicable roles, commissions plans. Our cash compensation range for this role is $180,000-$250,000. Final offers vary based on geography, candidate experience, relevant credentials, and other factors. Outstanding candidates may be eligible for adjusted terms plus meaningful equity. We are committed to pay equity and transparency. Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected vete