Key skills
Product ManagementInfrastructureData PlatformsStorageCloud ServicesPRD WritingUser Story WritingData Infrastructure for AICloud-native ArchitecturesMicroservicesContainersAPIsDistributed StorageCloud InfrastructureAWSAzureGCPKubernetesStakeholder ManagementAIAnalyticsLeadershipCommunicationSales
About this role
DataDirect Networks (DDN) is a global market leader in AI and high-performance data storage innovation. The Senior Product Manager will lead strategic product areas for Infinia, shaping product direction and driving alignment across teams while representing the product with senior customers and stakeholders.
Responsibilities:
- Define and drive the multi-release strategy and roadmap for major 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 strategic AI deployments
- Shape competitive strategy for Infinia in AI and cloud data infrastructure, including pricing/packaging input, win/loss analysis, and differentiation
- Use data (product analytics, customer feedback, financials) to drive portfolio-level decisions and trade-offs
Requirements:
- 7+ years of product management experience in infrastructure, data platforms, storage, 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 success metrics
- Experience working closely with sales, SEs, and customers on POCs, roadmap discussions, and escalations
- Excellent communication and stakeholder management skills across technical and non-technical audiences
- Bachelor's degree in computer science, Engineering, or related field, or equivalent practical experience
- Experience with data infrastructure for AI (training and inference pipelines, large-scale unstructured data, or AI factory architectures)
- Background in cloud-native architectures (microservices, containers, observability, APIs)
- Strong technical depth in at least one of: Distributed storage or data platforms (object, file, block, or key-value)
- Cloud infrastructure (AWS, Azure, GCP) or Kubernetes-based environments
- Prior experience in a B2B enterprise or high-growth infrastructure environment