Senior Product Manager

Who you are

• We don't expect the ideal candidate to check every box. The items below are what we look for; don't let a gap discourage you from applying
• 5+ years of product management on infrastructure products, with hands-on exposure to 2 or more platform families: ideally one public cloud (AWS, Azure, GCP, or their managed Kubernetes services) and one on-prem (vSphere, Nutanix, bare metal)
• Real Kubernetes depth: you understand cluster lifecycle, upgrades, and operators well enough to earn the respect of senior engineers and enterprise platform teams. Cluster API familiarity is a strong plus
• Judgment about maturity: this area includes fast-moving strategic work and stable surfaces that need discipline more than features. You can tell which is which and invest accordingly
• Comfort with upstream ecosystems: you understand what tracking upstream Kubernetes costs and buys. Participation in CNCF SIGs, working groups, or open source communities is a plus, not a bar
• Clear written communication across time zones and cultures
• CKA/CKAD or similar hands-on Kubernetes certification is a nice signal, never a requirement

What the job involves

• Kubernetes is becoming the common infrastructure abstraction under three classes of workloads: VMs, containers, and AI
• Multi-cluster management is where that abstraction becomes real, and it's the foundation the rest of our platform stands on
• Enterprises come to us with heterogeneous estates: public cloud and managed Kubernetes (AWS, Azure, Google Cloud, EKS, AKS, GKE, etc), on-prem (vSphere, Nutanix, bare metal), all built on Cluster API, some created with our platform, others built outside it
• Your job is to make every one of them a first-class citizen: declared, reconciled, and operated with the same rigor regardless of substrate, with no snowflakes
• You will own one of the most established product areas in the company, with a large enterprise and public sector customer base, and drive its next chapter: making multi-cluster infrastructure the substrate that AI workloads run on, adopting clusters built outside our platform as first-class citizens, keeping pace with upstream Kubernetes and Cluster API, and turning long-term support into a product enterprises can buy
• This is a deep domain role. You'll work daily with senior engineering leads and large enterprise customers
• It rewards technical fluency and judgment about what not to build
• What you will own:
• Infrastructure for AI workloads: bare metal and private cloud as the high-performance substrate for GPU clusters, in partnership with our AI product area. Multi-cluster is where AI factories actually run
• Cluster lifecycle across every substrate: provisioning, upgrades, scaling, and Day-2 operations for clusters on public clouds, private clouds, and bare metal, including the customer-facing side of platform transitions: when the ecosystem moves and clusters must follow, you own the migration experience and its communication
• Brownfield adoption and federation: the strategic direction of the area. Take clusters built outside our platform from read-only visibility to fully managed, without disruption
• Long-term support as a product: LTS for Kubernetes versions and workloads, vendor relationships that back it, and the version support policy customers plan against
• Estate organization and multi-tenancy: how enterprises carve up large cluster estates with tenant and team boundaries, shared versus dedicated clusters, bringing existing clusters under management, and the access and isolation model that makes one platform safe for many teams
• This map will evolve. The portfolio is growing faster than the org chart, and PMs here regularly take ownership of new product areas as they emerge, including products not yet announced. Expect your scope to expand as the platform does, deliberately and in dialogue with you
• How you will work:
• Evidence over opinion: usage telemetry and customer signals over the loudest voice, including your own
• Commitments are commitments: this area ships on release trains with enterprise customers planning around dates. Refined epics, explicit scope, honest slip communication
• One org: PM, UX, and Docs operate as a single group; you bring design and documentation in at the definition stage
• AI-native by default: we expect every PM to multiply their output with AI tooling, daily
• Remote-first across US, EU, and India time zones. Clear async writing is how decisions happen here
• Foundation product area with a loyal enterprise and public sector base, and a clear strategic direction into brownfield federation and AI infrastructure
• Small senior team, direct access to founders, engineering leadership, and customers
• Real ownership: this domain has one PM, and it's you

The application process

• Your time is valuable, so the process is short and each stage has a purpose:
• Screening interview (30 min): mutual fit and a walk through your experience
• Product interview (60 min): a working session on a real problem from this domain. We're looking at how you think, scope, and decide
• Technical depth interview (45 min): Kubernetes and infrastructure fluency, with one of our senior engineering leads
• Culture and team interview (30 min): working in a team setting, alignment with our core values