Product Manager

Komprise is looking for a technically strong Product Manager to drive product strategy, roadmap planning, and feature delivery for its unstructured data management platform. You will collaborate with Engineering, UX, Sales, Support, and Customer Experience teams to translate customer needs into impactful product solutions, from discovery through launch and adoption.

Responsibilities:

• Product Strategy: Define product vision, roadmap, and priorities for new and existing features.
• Product Execution: Own features end-to-end, from ideation and discovery to development, launch, and adoption.
• Stakeholder Management: Collaborate with Engineering, UX, Sales, Support, and CX teams to define requirements and technical specifications.
• Cross-functional Collaboration: Work with Engineering, QA, and Documentation teams to ensure high-quality product releases.
• Go-to-Market Enablement: Support product launches through training materials, enablement sessions, and technical documentation.
• Customer Insights: Analyze product usage, gather customer feedback, and prioritize enhancements based on business impact.
• Data-driven Decisions: Use analytics, customer insights, and AI tools to accelerate research and product execution.

Requirements:

• 2-5 years of experience as a product manager, with demonstrated experience delivering features from discovery to launch.
• Bachelor's or master's degree in computer science, electrical engineering, or a related field, OR prior experience as a software engineer or designer.
• Strong technical understanding of software architecture, APIs, and system trade-offs.
• Analytical mindset with the ability to make data-driven product decisions.
• Strong communication, stakeholder management, and problem-solving skills.
• User-centric approach with the ability to understand customer needs.
• Experience using AI tools for product research and execution.

Good to Have:

• Experience in data storage, data management, cloud infrastructure, or enterprise software.
• Familiarity with file and object storage protocols such as NFS, SMB, and CIFS.
• Exposure to data pipelines, metadata enrichment, AI/ML, or data preparation for AI.
• Experience working with globally distributed teams across time zones.