Product Manager, AI Data Pipelines & Developer Community Komprise

Company Overview

Data is growing exponentially as the world becomes more digitized. IDC states that there will be 175 zettabytes by 2025. Over 90% of this data is unstructured, consisting of video files, audio files, MRIs, log files, and more. AI requires unstructured data to properly train LLMs and unstructured data requires AI to extract value and add structure. Komprise is at the crossroads of these two huge tailwinds: unstructured data and AI.

Komprise powers the connection between unstructured data management and AI. Komprise Intelligent Data Management delivers a single platform to easily analyze, migrate, transparently tier and manage the lifecycle of petabytes of file and object data across hybrid environments. With Komprise, enterprise IT gains full visibility across silos to optimize storage, backup, ransomware and cloud costs. Komprise Smart Data Workflows and the Komprise Global File Index unlock unstructured data insights and access for AI.

Komprise is recognized as the leader in unstructured data management by analysts such as Gartner and Giga Om, and has been selected by Inc 5000 and Deloitte 500 for its high rate of growth.

Komprise customers include the who’s-who of enterprises across financial services, media and entertainment, healthcare, genomics, manufacturing, and public sectors. Komprise has a notably strong partner ecosystem: AWS, Azure, IBM, Pure Storage, and Net App are all resellers of Komprise.

As a Product Manager for AI Data Pipelines & Developer Community, you will be instrumental in bridging the gap between cutting‑edge AI data infrastructure and a thriving developer ecosystem. You will lead the strategy, roadmap, and execution of scalable, efficient AI data pipelines that power our AI‑driven products and empower our internal and external developer community to build innovative solutions on our platform.

We are looking for a go‑getter who is self‑motivated and thrives in an entrepreneurial environment, who takes initiative and appreciates the unique opportunity to define a product from the ground‑up.

• Define and Drive Product Strategy: Develop and communicate a clear vision and roadmap for the AI data pipeline platform and associated developer tools, ensuring alignment with business goals and market needs.
• Build and Optimize AI Data Pipelines: Work closely with our product team and IT, end‑users, data engineers and data scientists from our customers to build, optimize, and maintain scalable data pipelines that allow them to enrich, classify, curate data for AI agents for augmentation and inferencing.
• Translate User Needs into Product Requirements: Gather and prioritize user requirements, translating them into detailed product specifications and coordinating development efforts with engineering and data science teams.
• Champion Developer
  
  Experience:
  
  Understand the needs of the developer community, both internal and external, and develop tools, resources, and programs that enhance their experience building with our AI data platform. Investigate participation in partner developer communities and open‑source communities.
• Grow and Engage the Developer Community: Lead efforts to foster a vibrant developer community, potentially through events, forums, technical content, and strategic outreach.
• Measure and Analyze Product Performance: Define and track key metrics to measure the success and impact of both the AI data platform and community engagement efforts, using data‑driven insights to iterate and improve.
• Cross‑Functional
  
  Collaboration:
  
  Partner effectively with cross‑functional teams, including engineering, marketing, sales, and customer success, to ensure product vision alignment and drive successful execution.
• Stay Ahead of the Curve: Monitor industry trends, emerging technologies, and competitive offerings related to AI, data infrastructure, and developer ecosystems.

• Product Management
  
  Experience:
  
  Proven experience in product management, particularly with a focus on data and AI‑driven products.
• Technical Acumen: Strong understanding of technical data architectures, machine learning models, and AI applications in a business…