What You'll Be Doing

• Own a product area of our platform (for example GPU and AI workloads, node consolidation, or workload optimization) and its roadmap, with clear outcomes.
• Turn customer signals from Gong calls, field escalations, and live cluster data into well-scoped specs that engineers trust.
• Work with R&D on design and tradeoffs, with close attention to safety and risk in customers' production clusters.
• Lead discovery directly with platform, SRE, and FinOps teams to understand their workflows, pain points, and objections.
• Own the launch of what you ship: release checklist, docs, and field enablement, so Sales and CS know what to tell customers.
• Define and track the metrics that show whether what you shipped worked: adoption, automation coverage, realized savings, and how fast field asks are resolved.
• Conduct competitive research and work with the GTM team on positioning.
• Use AI tools and agents as part of how you work: research, analysis, specs, and small internal tools.

What You'll Bring

• 3+ years as a Product Manager on infrastructure, DevOps, cloud, or developer-platform products.
• Hands-on Kubernetes and cloud knowledge: you can read a manifest, explain requests, limits, and autoscaling, and reason about the risk of a change in production.
• A track record of shipping features customers adopted, with the numbers to show it.
• Comfort with data: you can write a query or dig into a dashboard yourself.
• Clear writing in English: your specs and customer-facing explanations hold up on their own.
• AI-native, or eager to be: you build small tools and automations instead of waiting for them.
• Nice to have: GPU or ML infrastructure, FinOps, or experience in a field-facing role (SE, TAM).