Job description

About Dragonfly Dragonfly is a global investment firm focused on the future of money, markets, and intelligence. With origins in crypto and over $3.5 billion in assets under management, we invest in generational companies and protocols across the frontier of finance and technology. We're a team of seasoned VCs, technologists, and markets experts with deep roots in New York, Silicon Valley, and Asia. We've published some of the industry's most widely read research on stablecoins, market structure, decentralized finance, networks, protocol security, and increasingly, the intersection of finance and AI. This is not a listing for an internal role at Dragonfly. We’re actively sourcing for a Product Manager, Models at one of our portfolio companies building a large scale consumer AI platform. This is not an ML research role. You will own the model portfolio end to end, treating models as product lines and making strategic calls about selection, positioning, and the end-user experience across every surface. Location: USA What We Are Looking For: • 5+ years in product management, ideally across infrastructure, dev tools, or AI/ML platforms • Real technical fluency, you can triage model and configuration issues before escalating to engineering • Comfort reasoning about unit economics, COGS, and cost/speed tradeoffs with incomplete data • Experience operating in fast moving environments where model releases land weekly • Comfortable with the tooling: APIs, inference systems, observability data, evaluation tooling • You align with the company’s product philosophy and can operationalize it • Bonus: experience with model configurations or AI infrastructure About the Role: • Own the model portfolio end to end, decide what lives on the platform and what doesn’t • Define and maintain model tiering across multiple product tiers and product lines • Build the models-as-product operating system: launch processes, config standards, uptime SLAs, deprecation policies, runbooks • Drive reliability: define health standards, monitor uptime, triage incidents, lead post-mortems, and track key inference performance metrics • Be the single source of truth on the model landscape, track provider changes, pricing shifts, and new releases • Own model strategy per product, map models to use cases across every product surface • Turn evaluation results, usage patterns, and customer feedback into roadmap recommendations • Work across Engineering, API, BI, Product, and Marketing, make strategic calls and ensure they ship Even if you don't match every point above, we encourage you to apply. There may be other opportunities that fit your skill set. Process: • We’ll confidentially match you with portfolio companies aligned with your experience, focus, and interests • If mutual interest exists between you and a team, we’ll facilitate a warm introduction • If there isn’t a match today, we’ll keep you top of mind for future opportunities Compensation • Early: $95,000–$130,000 • Mid: $130,000–$190,000 • Senior: $180,000–$250,000 The compensation range reflects variation by seniority, location, and hiring company. Final compensation is confirmed with the specific hiring company. Please submit your information below, and we’ll be in touch if there is a potential fit.

Requirements

Must-haves

5+ years in product management, ideally across infrastructure, dev tools, or AI/ML platforms
Real technical fluency, you can triage model and configuration issues before escalating to engineering
Comfort reasoning about unit economics, COGS, and cost/speed tradeoffs with incomplete data
Experience operating in fast moving environments where model releases land weekly
Comfortable with the tooling: APIs, inference systems, observability data, evaluation tooling
You align with the company’s product philosophy and can operationalize it
Own the model portfolio end to end, decide what lives on the platform and what doesn’t
Define and maintain model tiering across multiple product tiers and product lines
Build the models-as-product operating system: launch processes, config standards, uptime SLAs, deprecation policies, runbooks
Drive reliability: define health standards, monitor uptime, triage incidents, lead post-mortems, and track key inference performance metrics
Be the single source of truth on the model landscape, track provider changes, pricing shifts, and new releases
Own model strategy per product, map models to use cases across every product surface
Turn evaluation results, usage patterns, and customer feedback into roadmap recommendations
Work across Engineering, API, BI, Product, and Marketing, make strategic calls and ensure they ship
Even if you don't match every point above, we encourage you to apply. There may be other opportunities that fit your skill set.
We’ll confidentially match you with portfolio companies aligned with your experience, focus, and interests
If mutual interest exists between you and a team, we’ll facilitate a warm introduction
If there isn’t a match today, we’ll keep you top of mind for future opportunities

Nice-to-haves

Bonus: experience with model configurations or AI infrastructure

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlapi

Platform: gem
Effort: medium

Benefits

Benefits detected in the listing.

Pto