Head of Product - AI Infrastructure

About SpiNNcloud

SpiNNcloud is a deep-tech company building next-generation AI and compute infrastructure for a world where brute-force scaling is reaching its limits. Our architecture is designed to exploit sparsity at scale, focusing compute where it matters most while reducing unnecessary computation. We believe the next wave of AI infrastructure will be defined not only by raw performance, but by efficiency, system-level design, and the ability to deliver differentiated value on real workloads.

As we expand our focus on AI inference, we are looking for product leadership that can connect technology direction, market opportunity, and product strategy — helping define where we can win, why we win, and how we bring that to market.

About the Role

SpiNNcloud is hiring a Head of Product – AI Infrastructure to lead product strategy and execution for our AI infrastructure portfolio, with an initial focus on AI inference.

This is a senior leadership role with end-to-end responsibility across market discovery, competitive positioning, product requirements, roadmap direction, cross-functional execution, and go-to-market readiness.

You will work closely with Engineering and Research to translate technical differentiation into compelling products, and partner with Marketing and Sales to turn product advantages into clear narratives and measurable customer value. You will play a central role in defining where we win, why we win, and how we bring those advantages to market.

What You’ll Do

Product Strategy and Market

* Define and drive product strategy for SpiNNcloud’s AI infrastructure offerings, with a strong focus on inference workloads and emerging AI system requirements

* Build a sharp understanding of the AI inference and LLM market, including buyer needs, adoption patterns, evaluation criteria, and key technology trends

* Identify high-value segments, workloads, and deployment scenarios where we can deliver differentiated value across cost, performance, latency, throughput, efficiency, and deployment model

* Translate market insight into clear product priorities, investment areas, and long-term direction

Competitive and Ecosystem

* Maintain a deep understanding of the competitive landscape across chips, systems, cloud offerings, and inference software stacks

* Understand ecosystem dynamics across hardware, software, models, deployment environments, and customer buying criteria

* Turn competitive insight into differentiated positioning, product requirements, and roadmap priorities

* Identify partnership, ecosystem, and build-vs-buy opportunities that strengthen SpiNNcloud’s market position

Roadmap and Execution

* Own the product roadmap for AI infrastructure, balancing near-term execution with long-term strategy

* Partner with Engineering and Research to define product requirements, milestones, and success metrics

* Drive prioritization with clear trade-offs, business rationale, and customer impact

* Ensure execution remains grounded in customer needs and measurable outcomes

* Lead alignment across Product, Engineering, Research, Sales, and Marketing

Go-to-Market and Commercial Enablement

* Partner with Marketing on messaging, launches, and content strategy

* Support Sales with high-quality enablement assets, including pitch narratives, competitive battlecards, FAQs, case studies, and evaluation guidance

* Help define how product value is communicated to technical and business stakeholders

* Act as a senior product voice in customer, partner, and market-facing conversations

Technical Storytelling and Thought Leadership

* Shape clear, credible technical narratives around SpiNNcloud’s products, differentiation, and market positioning

* Create and guide technical content such as blogs, whitepapers, solution briefs, product documentation, and presentations

* Articulate “why we win” in a way that resonates with both technical evaluators and executive buyers

* Represent the product vision internally and externally with clarity and authority

Data-Driven Product Leadership

* Use data to inform decisions, including benchmark analysis, workload characterization, and performance-efficiency trade-off evaluation

* Guide evaluation frameworks that connect technical performance to customer value

* Support product decisions with structured analysis and lightweight tooling where helpful

What We’re Looking For

The more of the following you bring, the stronger the fit:

* Significant product leadership experience in AI infrastructure, semiconductors, accelerators, cloud infrastructure, or related technical markets

* Strong semiconductor and accelerator expertise, including familiarity with GPUs, TPUs, and alternative AI architectures

* Strong understanding of how customers evaluate system trade-offs such as performance, throughput, latency, deployability, and operational efficiency

* Strong machine learning and AI systems understanding, ideally supported by advanced academic training or substantial hands-on experience in ML, AI infrastructure, or related domains

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

* Proven success working closely with Engineering and Research teams in technically complex environments, driving alignment, trade-offs, and execution

* Strong grasp of the AI inference ecosystem, including infrastructure layers, deployment models, and workload requirements

* Strong written and verbal communication skills, including the ability to create clear product narratives and technically credible content for internal and external audiences

* Strong commercial instincts and stakeholder management skills, with the ability to align teams and drive decisions across Product, Engineering, Sales, Marketing, and leadership

* High ownership, strategic judgment, and execution focus

* Basic programming proficiency and comfort engaging with technical artifacts, benchmarks, and analysis

Nice to Have

* Experience with AI inference products, LLM infrastructure, or model-serving systems

* Experience bringing deep-tech or infrastructure products from concept to market

* Familiarity with benchmarking methodologies and workload evaluation in production environments

* Experience working in startup or scale-up environments where strategic ambiguity and hands-on execution go together