Principal Product Manager - AI & HPC Data Infrastructure

Doist; Santa Clara (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

DDN seeks a Principal Product Manager to lead strategic product areas for EXAScaler. You will shape product direction, align multiple teams, and represent the product with senior customers and internal stakeholders.

You will drive roadmaps, PRDs, and user stories, and collaborate with engineering to balance innovation with reliability. Strong focus on data-driven decision making and market differentiation in AI/HPC deployments.

Qualifications

• 12+ years of product management experience in infrastructure, data platforms, storage, HPC environments, or cloud services.
• Proven track record delivering production features from definition through launch and iteration.
• Excellent communication and stakeholder management across technical and non-technical audiences.

Responsibilities

• Define and drive the multi-release strategy and roadmap for EXAScaler product domains.
• Translate strategy into prioritized roadmaps, PRDs, and detailed user stories with measurable success criteria.
• Partner with engineering leadership to align architecture, investment, and sequencing decisions.
• Act as a senior product voice with customers and partners, including executive briefings and roadmap deep dives.
• Shape competitive strategy for EXAScaler, including pricing, packaging, and market differentiation.
• Use data (analytics, feedback, and financial performance) to drive portfolio-level decisions.

Skills

Product management

Infrastructure

Data platforms

Storage

HPC environments

Cloud services

Communication

Stakeholder management

Education

Bachelor’s degree in Computer Science/Engineering or related field

Job description

DDN seeks a Principal Product Manager to lead strategic product areas for EXAScaler. You will shape product direction, align multiple teams, and represent the product with senior customers and internal stakeholders.

You will drive roadmaps, PRDs, and user stories, and collaborate with engineering to balance innovation with reliability. Strong focus on data-driven decision making and market differentiation in AI/HPC deployments.