Sr Product Manager - AI Cloud
The Mission
Our AI Cloud is the strategic engine that proves our hardware dominance and enables our entire business. We need a Principal Product Manager to define how this cloud drives velocity across our Enterprise, Managed Service, and On-Premise product lines. You will own the strategy for using our cloud to showcase our unique hardware advantages and unlock high-value enterprise use cases.
Key Responsibilities
Strategic Direction & Business Velocity
Unified Cloud Strategy: Define the AI Cloud vision to serve as the enabling vehicle for our two core GTM motions: SambaStack and SambaManaged.
Hardware-Software Synergy: Translate our silicon advantages into cloud features and model serving strategies that competitors cannot replicate.
Solution Incubation: Identify and incubate unique solution architectures on our cloud that prove high-value use cases for enterprise customers.
Product Roadmap & Execution
Roadmap Ownership: Drive the end-to-end cloud roadmap towards a cohesive strategy. Prioritize features that solve enterprise inference challenges and enable our partners to build profitable businesses.
Model Strategy: Decide what models we serve and why. Align the portfolio to customer use cases and hardware strengths.
Technical Definition: Author clear, rigorous PRDs solutions and new features. Lead the software release strategy to ensure consistent delivery.
Market Positioning & Economics
Value Proposition: Define the narrative. Articulate exactly how our cloud unlocks our sales motions and drive the tactics to lead to success.
Tokenomics & Pricing: Master the unit economics of the cloud. Own the cost/margin analysis and pricing strategy to ensure we win deals while protecting business viability.
Competitive Intelligence: Maintain deep knowledge of the compute landscape to position our offering effectively against theirs.
The Profile
8+ Years Experience: Product ownership in Cloud Infrastructure, AI/ML, or Compute Platforms.
Strategic Architect: You understand how a cloud product enables hardware sales. You see the link between API features and deal velocity.
AI Native: Deep understanding of the inference market, LLM serving challenges, and the compute provider landscape.
Technical & Analytical: You can write a technical PRD, model unit economics, and debate strategy with product and engineering leadership.
Ways to Standout
Hardware-Software Fluency: Deep understanding of AI accelerators and how hardware architecture dictates inference performance.
Inference Market Expertise: Intimate knowledge of the inference landscape—including hyperscalers and specialized providers—and how to effectively position against them.
Bottleneck Analysis: Technical ability to identify critical value blockers in AI inference (latency, throughput, cost) and how our cloud solves them.
Economic Rigor: Capability to model complex cloud unit economics, including tokenomics, margin analysis, and the P&L impact of optimizations.
Enterprise Strategy: Clear vision for enterprise AI adoption, understanding the specific requirements for security, scalability, and managed services.