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Spectro Cloud is an AI and Kubernetes infrastructure platform serving demanding enterprise environments. The company enables organizations to manage complete infrastructure stacks—from bare metal to production AI—across data centers, clouds, edge, and air-gapped environments at fleet scale.
You will own the multi-cluster management product area, a foundational component of the platform. This is a deep domain role requiring daily collaboration with senior engineering leads and large enterprise customers. The position rewards technical fluency and sound judgment about prioritization.
Key ownership areas:
**Infrastructure for AI Workloads**: Drive bare metal and private cloud as high-performance substrates for GPU clusters, partnering with the AI product team. Multi-cluster management is where AI factories actually operate.
**Cluster Lifecycle Across All Substrates**: Own provisioning, upgrades, scaling, and Day-2 operations for clusters on public clouds, private clouds, and bare metal. Manage the customer-facing experience during platform transitions and migrations.
**Brownfield Adoption and Federation**: Lead the strategic direction to take clusters built outside the platform from read-only visibility to fully managed operation without disruption.
**Long-Term Support as a Product**: Define LTS strategy for Kubernetes versions and workloads, manage vendor relationships, and establish version support policies customers can plan against.
**Estate Organization and Multi-Tenancy**: Shape how enterprises organize large cluster estates with tenant and team boundaries, shared versus dedicated clusters, and access/isolation models.
The portfolio grows faster than the org chart; expect your scope to expand deliberately as the platform evolves.
**Working Style**: Evidence-driven (usage telemetry and customer signals over opinion). Commitments are firm—this area ships on release trains with enterprise customers planning around dates. PM, UX, and Docs operate as one group; you bring design and documentation into definition stages. AI-native by default; daily use of AI tooling expected. Remote-first across US, EU, and India time zones with async-first decision-making.
**Requirements**:
- 5+ years of product management on infrastructure products with hands-on exposure to 2+ platform families (ideally one public cloud—AWS, Azure, GCP, or managed Kubernetes services—and one on-prem: vSphere, Nutanix, bare metal)
- Real Kubernetes depth: understand cluster lifecycle, upgrades, and operators well enough to earn respect of senior engineers and enterprise platform teams
- Cluster API familiarity is a strong plus
- Judgment about maturity: distinguish between fast-moving strategic work and stable surfaces requiring discipline over features
- Comfort with upstream ecosystems; understand the cost and benefit of tracking upstream Kubernetes
- Participation in CNCF SIGs, working groups, or open source communities is a plus
- Clear written communication across time zones and cultures
- CKA/CKAD or similar hands-on Kubernetes certification is a nice signal, never a requirement
