Job description

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. 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. Responsibilities 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: Market intelligence to product inputs 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. Competitor specifications and roadmaps 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. AI tooling for intelligence 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. Segment and demand theses 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. Intelligence cadence 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. How We Measure This Role 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. Basic Qualifications 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. Additional Required Qualifications 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. Preferred Qualifications 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. Base Salary Range: Base Pay Range $216,000 — $260,000 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

Requirements

Must-haves

Market intelligence to product inputs
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.
Competitor specifications and roadmaps
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.
AI tooling for intelligence
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.
Segment and demand theses
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.

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Benefits

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