Jobgether
Technical Product Manager, AI Storage
- Remote
- full time
- Posted today
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About the role
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Technical Product Manager, AI Storage based in United States.
This role offers the opportunity to define the storage foundation powering the next generation of AI infrastructure.
You will own the vision, roadmap, and priorities for storage capabilities supporting large-scale GPU training and inference.
Working at the intersection of high-performance computing, Kubernetes, and cloud infrastructure, you will turn complex storage technologies into a coherent, declarative product experience.
You will collaborate closely with engineering, architecture, marketing, field teams, customers, and ecosystem partners to bring strategic capabilities to market.
Your work will influence how GPU clouds, sovereign clouds, NeoClouds, and AI-focused enterprises provision, automate, protect, and scale data.
This is a highly technical product leadership opportunity with significant influence over product strategy and go-to-market positioning.
You will help shape an open, scalable, and production-ready storage platform for the rapidly evolving AI cloud ecosystem.
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Accountabilities
Own the vision, strategy, roadmap, and feature priorities for AI storage, defining how customers provision, automate, operate, tier, protect, and scale storage across GPU clusters.
Translate requirements from GPU cloud operators, NeoClouds, telecommunications providers, sovereign clouds, and enterprise platform teams into clear product direction and actionable requirements.
Partner closely with engineering and architecture teams to define product requirements, assess technical trade-offs, and deliver secure, scalable, reliable storage capabilities.
Manage and prioritize the product backlog using customer feedback, production deployment insights, design-partner input, and evolving market requirements.
Shape capabilities across parallel and distributed file systems, S3-compatible object storage, block storage, snapshots, data protection, automated tiering, and other storage technologies.
Define product positioning, packaging, messaging, and competitive differentiation for AI storage solutions.
Develop field-facing materials such as technical briefs, competitive battlecards, reference architectures, and other resources that support customer engagement and sales execution.
Act as the storage product lead for strategic accounts, helping field teams translate complex technical capabilities into compelling customer solutions.
Represent the product at industry events, analyst briefings, and customer advisory boards while building relationships with storage, silicon, and technology ecosystem partners.
Drive alignment between storage, GPU infrastructure, Kubernetes, and AI workload requirements to create a unified and declarative product experience.
Requirements
5+ years of experience in product management, technical product management, or a senior technical position with ownership of a storage product, platform, or large-scale storage environment.
Strong technical knowledge of classical and modern storage technologies, including parallel and distributed file systems such as Lustre, GPFS/Spectrum Scale, BeeGFS, WEKA, VAST, or DAOS.
Hands-on familiarity with S3-compatible object storage and block storage environments operating at significant scale.
Strong understanding of Linux storage, Kubernetes storage concepts such as CSI, dynamic provisioning and storage classes, software-defined storage, storage automation, and hyperscale or service-provider infrastructure.
Practical experience with modern GPU cluster storage, including GPUDirect Storage, RDMA data paths, NVMe-oF, high-throughput ingestion pipelines, and hot/warm/cold storage tiering for training datasets and checkpoints.
Ability to translate highly technical customer and engineering requirements into clear product strategies, priorities, and roadmaps.
Strong product judgment and ability to evaluate technical trade-offs while balancing customer needs, scalability, reliability, security, and business objectives.
Excellent communication and collaboration skills, with the ability to engage effectively with engineers, architects, customers, executives, field teams, and technology partners.
Ability to operate effectively in a distributed, fast-moving environment characterized by open-source innovation, technical complexity, and continuous change.
Benefits
Competitive compensation package with strong benefits and stock options.
Opportunity to work with cutting-edge open-source cloud and AI infrastructure technologies.
Collaboration with highly skilled and passionate colleagues working with major enterprise customers.
Professional development and training opportunities.
Opportunities to attend industry conferences, technical working groups, and ecosystem events.
Customized workstation, with macOS or Windows options.
High-energy environment that values openness, collaboration, technical excellence, risk-taking, and continuous growth.
Opportunity to influence the future of AI infrastructure and work directly with GPU cloud operators, sovereign clouds, and AI-focused enterprises.
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How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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Skills
- Product management
- Storage technologies
- AI infrastructure
- Kubernetes
- Cloud infrastructure
- Distributed file systems
- S3-compatible object storage
- Block storage
- Linux storage
- Storage automation
- GPU cluster storage
- GPUDirect Storage
- RDMA
- NVMe-oF
- Data tiering
- Product strategy
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