At Fluidstack, we’re building the infrastructure for abundant intelligence. We partner with top AI labs, governments, and enterprises - including Mistral, Poolside, Black Forest Labs, Meta, and more - to unlock compute at the speed of light.
We’re working with urgency to make AGI a reality. As such, our team is highly motivated and committed to delivering world-class infrastructure. We treat our customers’ outcomes as our own, taking pride in the systems we build and the trust we earn. If you’re motivated by purpose, obsessed with excellence, and ready to work very hard to accelerate the future of intelligence, join us in building what's next.
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.
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
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
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 veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.
fluidstack