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SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for enterprises, AI labs, service providers, neo-clouds, and sovereign AI initiatives worldwide. SambaStack combines rack-scale hardware, optimized open-source models, and a serving platform to enable customers to deploy state-of-the-art models with superior performance, lower total cost of ownership, and rapid time to value. Built on SambaNova's Reconfigurable Dataflow Unit (RDU), its dataflow architecture delivers low-latency, high-throughput inference on large models, with industry-leading decode performance that is especially impactful for agentic workloads such as multi-turn agents, code generation, and long-running applications.

SambaNova is hiring a Principal Product Manager, Product Strategy and Competitive Intelligence to turn market intelligence into decisions that shape our product and business. The role translates third-party research, competitor disclosures, and benchmark data into roadmap, pricing, and positioning decisions, while building AI-powered tooling to make that intelligence faster, deeper, and more scalable. The ideal candidate can build a TCO model from primary inputs, connect architecture specifications to financial performance, and go hands-on with AI tools to automate and continuously improve their own research pipeline.  This individual will be responsible for:

• Own the pipeline from third-party research (SemiAnalysis TCO, Tokenomics, Accelerator, and Datacenter models; competitor disclosures; benchmark data) to decision-ready analysis.
• Maintain the house model of where RDU inference wins on cost per million tokens, at which latency tiers, for which workloads, and against which competitor configurations.
• Convert TCO, tokenomics, and data center data into roadmap language: feature priorities, pricing moves, and segment bets.
• Open each product review with a summary of market changes since the last quarter and their implications for SambaNova.

• Track chip-level specifications for NVIDIA, AMD, Google TPU, AWS Trainium, Cerebras, Groq, and emerging accelerators: compute, memory hierarchy (SRAM, HBM, DDR), interconnect, power, process node, and packaging.
• Track rack- and cluster-level design: scale-up and scale-out topology, networking (NVLink-class fabrics, Ethernet and InfiniBand, optics), storage, cooling, and rack power density.
• Track roadmaps: announced parts, credible leaks, and supply signals such as HBM allocation, CoWoS capacity, and foundry node ramps.
• When a spec or roadmap change moves the TCO or latency frontier, quantify the effect on SambaNova's positioning within a week.
• Maintain a versioned spec comparison matrix with a changelog.

• Build agentic pipelines that monitor research releases, competitor announcements, InferenceMAX and ClusterMAX updates, conference disclosures (Hot Chips, GTC, OCP), and regulatory and supply-chain filings.
• Extract specs and claims into the comparison matrix automatically, with human review on anything that feeds a decision.
• Automate the first draft of the weekly brief from monitored sources.
• Treat the tooling as a product and iterate on precision, coverage, and detection latency.

• Use data center capacity and power data to pressure-test the SambaManaged pipeline: which operators have stranded power and cooling suited to air-cooled RDU racks, where, and on what timeline.
• Track workload mix shifts (agentic, chat, coding) and what they imply for decode-optimized positioning.
• Keep a short list of falsifiable house theses and score them quarterly against outcomes.

• Write a weekly two-page brief covering what changed, what it means, and which decision is needed from whom.
• Produce a monthly deep dive tied to one live roadmap question.
• Run a quarterly thesis review with the product and executive teams.
• Set the analytical agenda for SambaNova's external research relationships, including the questions to raise on analyst calls and the custom data pulls to request. Another team member manages the vendor relationships and access. This role sets the questions and turns the outputs into product inputs.

We measure this role by the product, pricing, and investment decisions its analysis changes, not by the volume of reports or summaries produced. Automated tooling handles monitoring and first drafts. The person in this role is accountable for the conclusions SambaNova draws from them.

• 8+ years in semiconductor or AI infrastructure analysis, competitive intelligence, equity research, corporate or product strategy at a chip, cloud, or AI infrastructure company.
• Has built quantitative market or economic models (accelerator forecasts, TCO, capacity and demand) from primary inputs.
• Bachelor's degree in engineering, computer science, economics, or another quantitative field, or equivalent experience.

• Fluent in accelerator and system architecture (compute, memory hierarchy, interconnect, power) and how each drives inference performance and cost.
• Track record of translating competitor spec and roadmap changes into product, pricing, or investment decisions.
• Hands-on with Python and LLM APIs, and able to build or direct agentic research tooling (extraction pipelines, monitoring agents) without waiting on an engineering team.
• Concise, quantified, executive-ready writing with stated uncertainty.

• Direct experience with SemiAnalysis models (TCO, Tokenomics, Accelerator, ClusterMAX, InferenceMAX) or comparable institutional research.
• Depth in inference economics: cost per million tokens, latency and throughput tradeoffs, prefill and decode disaggregation, and workload mix.
• Rack- and cluster-level fluency: networking, optics, cooling, power density, and scale-up and scale-out topologies.
• Has done capacity planning or GPU economics at a cloud, neocloud, or hyperscaler.
• Has written an investment thesis that redirected a roadmap or a capital allocation, or built a decision framework that others kept running.
• Willing to challenge a senior stakeholder's figures when the evidence supports it.