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Senior Product Manager, ExaScaler

ddn · Remote - Connecticut
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DDN is seeking a Principal Product Manager to lead strategic product areas for EXAScaler. This role shapes product direction, drives cross-team alignment, and represents the product with senior customers and internal stakeholders. Key Responsibilities • Define and drive the multi-release strategy and roadmap for major EXAScaler product domains. • Translate strategy into prioritized, outcome-driven roadmaps, clear PRDs, and detailed user stories with measurable success criteria. • Partner with engineering leadership to make architecture, investment, and sequencing decisions, balancing innovation with reliability and technical debt reduction. • Act as a senior product voice with customers and partners, including executive briefings, roadmap deep dives, and joint solution planning for large-scale AI and HPC deployments. • Shape competitive strategy for EXAScaler in AI and high-performance data infrastructure, including pricing and packaging input, win/loss analysis, and market differentiation. • Use data (product analytics, customer feedback, and financial performance) to drive portfolio-level decisions and product investment trade-offs. Qualifications Must Have • 12+ years of product management experience in infrastructure, data platforms, storage, HPC environments, or cloud services. • Proven track record of delivering production features at scale, from definition through launch and iteration. • Demonstrated ability to write concise PRDs and user stories with clear acceptance criteria and measurable success metrics. • Experience working closely with sales teams, solutions architects, and customers on proof-of-concepts, roadmap discussions, and product escalations. • Excellent communication and stakeholder management skills across both technical and non-technical audiences. • Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience. Nice to Have • Experience with data infrastructure supporting AI workloads, including training and inference pipelines or large-scale unstructured data environments. • Familiarity with parallel file systems and high-performance storage architectures. • Background in cloud-native architectures including microservices, containers, observability frameworks, and APIs. • Strong technical depth in at least one of the following: • Distributed storage or parallel file systems (Lustre, object, file, block, or key-value storage) • Cloud infrastructure platforms (AWS, Azure, GCP) or Kubernetes-based environments • Prior experience working in a B2B enterprise infrastructure company or high-growth technology environment.

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