Senior Product Manager – AI Infrastructure

This is a fully remote position, open to applicants in Germany.

📋 Description

• Take charge of the complete lifecycle of the AI inference product strategy.

• Conduct market exploration and competitive analysis.

• Establish requirements and implement the product roadmap.

• Prepare the product for market launch.

• Collaborate with Engineering and Research teams.

• Work with Marketing and Sales to convert technical distinctions into clear product stories and measurable customer benefits.

• Develop an understanding of the AI inference and LLM market, focusing on buyer needs, adoption trends, evaluation standards, and emerging developments.

• Identify high-value segments and use cases based on cost, performance, latency, throughput, energy consumption, and deployment models.

• Keep an updated overview of competitors and alternatives, including chips, systems, cloud services, and inference stacks.

• Convert competitive insights into product positioning, requirements, and roadmap priorities.

• Define product requirements, milestones, and success metrics in collaboration with Engineering and Research.

• Drive roadmap prioritization with clear trade-offs and rationale.

• Ensure that execution stays aligned with customer needs and measurable outcomes.

• Partner with Marketing on messaging, product launches, and content strategy.

• Assist Sales with pitch narratives, competitive battlecards, FAQs, case studies, and evaluation guidance.

• Create technical content, including blogs, whitepapers, solution briefs, product documentation, and presentations.

• Clearly articulate product differentiation to both technical and business stakeholders.

• Analyze benchmarks, workload characteristics, and performance/efficiency trade-offs.

• Develop lightweight Python tools and scripts to validate assumptions and support product decisions.

⛳️ Requirements

• Strong expertise in semiconductors and accelerators, including knowledge of GPUs and TPUs.

• Understanding of how customers evaluate hardware and system trade-offs, focusing on performance, throughput, latency, deployability, and operational efficiency.

• Profound knowledge of machine learning, ideally supported by a university degree or PhD, or significant experience in ML, AI systems, or a related field.

• Solid grasp of ML concepts and inference methodologies.

• Proven ability to translate technical knowledge into product strategy, encompassing segmentation, positioning, differentiated requirements, and roadmap prioritization.

• Successful track record of working with Engineering and Research teams in complex technical settings, driving alignment, trade-offs, and execution.

• Basic programming skills and comfort working with technical documents.

• Excellent written and verbal communication abilities.

• Ability to create clear technical narratives and enablement content for both internal and external audiences.

• High sense of ownership and strong stakeholder management skills.

• Capacity to drive decision-making, align cross-functional teams, and achieve outcomes.

🏝️ Benefits

• Full-time employment.

• Remote work opportunities.