Director, AI Product Management

MinIO provides the data and memory foundation for enterprise AI through products that support AI, analytics, inference, and data platform workloads. The Director of AI Product Management will lead growth strategy, partnerships, customer and buyer engagement, positioning, field enablement, pricing and packaging, competitive intelligence, and product direction for Data Intelligence products.

Responsibilities:

• Growth strategy for our Data Intelligence products — where we play, who we sell to, how we win, and the sequencing of bets that gets us there
• Partnerships — work closely with key partners to develop ground breaking products
• The customer and buyer motion — being in front of inference platform teams, data platform leads, and the buyers who decide. Joining strategic deals. Running the win/loss loop and feeding it back into strategy
• Positioning and narrative — partnering with Marketing on how the AI stories land in market, what we publish, and how a first-time buyer encounters MinIO
• Field partnership — building the assets sellers actually use, supporting the deals that matter, making sure the field can run an inference-buyer or lakehouse-buyer conversation confidently
• Pricing and packaging — how Data Intelligence products are sold, how the AI and Analytics motions are priced differently if they should be, how we capture value as workloads grow
• Competitive intelligence — knowing the AI training inference competitive landscape, and shaping how we differentiate
• Partner GTM for AI — the AI ecosystem is partner-heavy, and unlocking it is part of the role
• Influence on the product — through customer signal, pipeline data, and competitive insight you will be the most informed external voice in the room to influence direction

Requirements:

• 8+ years in product management, with at least 3 years on infrastructure, data, or AI/ML products sold to technical buyers
• Demonstrated fluency in modern AI and analytics stacks — you don't need to have trained a foundation model, but you should be conversant in how training and inference pipelines actually consume storage, key tradeoffs and why it matters, and how data platform teams make build/buy decisions
• A track record of working closely with field teams on real revenue — you've sat in on deals, you've built enablement that sellers actually used, you've changed a deal's outcome with a well-timed product conversation
• Partnership with marketing on crafting compelling narratives, presented at external conferences, webinars
• Strong analytical instincts — you reach for data to test your hypotheses, not to confirm them
• The ability to write clearly and think rigorously in writing. Most of the work that compounds in this role is written
• Excellent partnership with engineering — you've earned engineers' trust before by being technically credible and by making prioritization defensible
• Real comfort with pricing and packaging decisions  — if you've owned or co-owned them, not just commented on them, that's a big plus