Senior Product Manager

The Mission

SambaRack is SambaNova's hardware product for inference cloud providers who want direct access to RDU capabilities without adopting SambaNova's opinionated software stack. We need a Senior PM to drive execution - spec the work, coordinate delivery across engineering and field, and ensure SambaRack ships as a coherent, well-documented product that inference clouds can integrate with confidence.

Key Responsibilities

Product Specification & Execution

• Author clear, rigorous PRDs across SambaRack's core work-streams - inference engine integrations, containerized deployment artifacts, and bare metal and Kubernetes deployment paths
• Translate product definition into engineering-ready specifications with well-defined requirements and acceptance criteria
• Own the release roadmap - sequence work-streams, manage dependencies, and drive delivery against commitments

Customer & Field Engagement

• Work directly with customers as they integrate SambaRack - understand their integration challenges, surface product gaps, and feed them back into the roadmap
• Partner with field teams to ensure SambaRack is positioned and sold correctly against the ICP
• Own the feedback loop between early customers and engineering

Documentation

• Own SambaRack's documentation strategy - define what great looks like for a hardware integration product, and hold the team accountable to it
• Define and maintain the supported features list, compatibility matrix, and release notes

Go-to-Market

• Define the integration experience customers should have and hold engineering accountable to it
• Work with sales and marketing to ensure SambaRack's positioning is crisp

The Profile

• 5+ years of product management experience in infrastructure, compute platforms, or AI/ML systems
• Execution-oriented: You know how to take a defined product strategy and drive it to shipped software. You write good PRDs, run tight review cycles, and keep engineering moving
• Technical depth: You can hold a credible conversation with engineers about inference engine architecture, Kubernetes deployment patterns, and observability integrations. You don't need to write the code but you need to understand the tradeoffs
• Customer-facing: You have direct experience working with infrastructure or platform engineering teams during technical integrations or evaluations. You understand their operational priorities and can translate their feedback into product requirements
• OSS-aware: You understand what it means to ship and maintain an open source artifact - community support, release cadence, compatibility commitments, and documentation expectations

Ways to Stand Out

• Inference infrastructure expertise: Deep familiarity with vLLM and how inference engines integrate with accelerator hardware
• Inference cloud fluency: You understand how inference cloud operators think - they want standard interfaces, minimal operational overhead, and hardware that slots into their existing toolchain
• Documentation as product: You treat documentation as a first-class product deliverable, not an afterthought. You know what good looks like for a hardware integration product