(Senior)Product Manager - AI Infrastructure

The Role

We are hiring a Product Manager or Senior Product Manager to own the end-to-end lifecycle of our AI inference product direction. This includes market discovery and competitive intelligence, requirements definition, roadmap execution, and go-to-market readiness. You will partner closely with Engineering and Research and collaborate with Marketing and Sales to translate technical differentiation into clear product narratives and measurable customer value.

Key Responsibilities

• Market research & strategy

• build a sharp understanding of the AI inference and LLM market (buyer needs, adoption patterns, evaluation criteria, and emerging trends)

• identifyhigh-value segments and use cases where we can win (cost, performance, latency, throughput, energy, deployment model, etc.)

• Competitive & ecosystem analysis

• maintain an up-to-date view of competitors and alternatives (chips, systems, cloud offerings, and inference stacks)

• translate competitive insights into positioning, requirements, and roadmap priorities

• Requirements & roadmap ownership

• work with Engineering and Research to define product requirements, milestones, and success metrics

• drive roadmap prioritization with clear tradeoffsand rationale

• ensure execution stays connected to customer needs and measurable outcomes

• GTM + sales enablement

• partner with Marketing on messaging, launches, and content strategy

• support Sales with enablement assets: pitch narratives, competitive battlecards, FAQs, case studies, and evaluation guidance

• Technical storytelling & content

• create crisp, credible technical content (blogs, whitepapers, solution briefs, product docs, and presentations)

• articulate “why we win” clearly to technical and business stakeholders

• Hands-on analysis

• use data to drive decisions: analyzebenchmarks, workload characteristics, and performance/efficiency tradeoffs

• build lightweight Python tools/scripts to validateassumptions and support product decisions

Qualifications

The more of the following qualifications you bring, the stronger the fit for this role:

• Strong semiconductor and accelerator expertise, including familiarity with GPUs and TPUs, and an understanding of how customers evaluate hardware and system trade-offssuch as performance, throughput, latency, deployability, and operational efficiency.

• Strong machine learning depth, ideally supported by a university degree/PhDor significant experiencein ML, AI systems, or a related area, with a solid understanding of ML concepts and inferencing.

• Demonstrated ability to translate technical insight into product strategy, including segmentation, positioning, differentiated requirements, and roadmap prioritization.

• Proven effectiveness working with Engineering and Research teams in technically complex environments, driving alignment, trade-offs, and execution.

• Basic programming proficiencyand comfort working with technical artifacts.

• Strong written and verbal communication skills, including the ability to produce clear technical narratives and enablement content for internal and external audiences.

• High ownership and strong stakeholder management, with the ability to drive decisions, align cross-functional teams, and deliver outcomes.