(Senior)Product Manager - AI Infrastructure

Role overview

Hiring a (Senior) Product Manager to own the end-to-end lifecycle of the company’s AI inference product direction, from market discovery through roadmap execution and go-to-market readiness.

Responsibilities

• Market research & strategy:
  • Build understanding of the AI inference and LLM market (buyer needs, adoption patterns, evaluation criteria, emerging trends)
  • Identify high-value segments and winning use cases (e.g., cost, performance, latency, throughput, energy, deployment model)
• Competitive & ecosystem analysis:
  • Maintain up-to-date views of competitors and alternatives (chips, systems, cloud offerings, inference stacks)
  • Translate competitive insights into positioning, product requirements, and roadmap priorities
• Requirements & roadmap ownership:
  • Partner with Engineering and Research to define requirements, milestones, and success metrics
  • Prioritize the roadmap with clear tradeoffs and rationale
  • Ensure execution stays connected to customer needs and measurable outcomes
• GTM + sales enablement:
  • Partner with Marketing on messaging, launches, and content strategy
  • Enable Sales with pitch narratives, competitive battlecards, FAQs, case studies, and evaluation guidance
• Technical storytelling & content:
  • Create crisp technical content (blogs, whitepapers, solution briefs, product docs, presentations)
  • Communicate “why we win” for technical and business stakeholders
• Hands-on analysis:
  • Use data to drive decisions (benchmarks, workload characteristics, performance/efficiency tradeoffs)
  • Build lightweight Python tools/scripts to validate assumptions and support product decisions

Requirements

• Strong semiconductor and accelerator expertise (familiarity with GPUs and TPUs) and understanding of customer evaluation across performance/throughput/latency/deployability/operational efficiency
• Strong ML depth (ideally degree/PhD or significant experience in ML, AI systems, or related areas)
• Ability to translate technical insight into product strategy (segmentation, positioning, differentiated requirements, roadmap prioritization)
• Proven ability to work with Engineering and Research in technically complex environments, aligning teams and driving tradeoffs
• Basic programming proficiency and comfort with technical artifacts
• Strong written and verbal communication skills to produce clear technical narratives and enablement content
• High ownership and strong stakeholder management

Nice to have

• Not explicitly stated, but the strongest fit comes from demonstrated deep experience across ML systems + inference evaluation and accelerator hardware tradeoffs.