Senior Product Manager – Agent Marketplace

US-CA-Menlo Park · 6+ years experience · Full-time · Hybrid · Posted Oct 13, 2026

At a glance

As a Senior Product Manager for the Marketplace, you will own the strategy and execution for making Snowflake the definitive destination where third-party AI agents are built, governed, distributed, and monetized.
You will act as a general manager operating at the intersection of platform engineering, developer ecosystems, and commercial strategy—connecting partner innovation directly to enterprise customer adoption.

Define the Strategic Vision: Set and socialize the product strategy for Snowflake’s AI-first marketplace, aligning product leadership, developer relations, partner engineering, and Go-To-Market (GTM) teams behind key primitive releases.
Ship Category-Defining Primitives: Own the end-to-end product lifecycle for third party agents, MCPs, Semantic Views and future AI Products.
Design Commercial Mechanics: Drive monetization design as a core product surface, including pricing and packaging, usage- and outcome-based billing and partner revenue-share structures.
Operate AI-Natively: Prototype listing workflows, build partner integrations, and utilize advanced telemetry and generative tools to inform roadmap prioritization and evaluate third-party agent performance hands-on.
Deliver Measurable Impact: Own overall business metrics, driving partner supply growth, enterprise buyer adoption of AI-first listings, and platform consumption pulled through agentic workflows.

6+ years in product management, with a track record of bringing AI, developer platform, or infrastructure products from 0-to-1 and scaling them to commercial adoption.
Proven background in building two-sided markets—such as developer platforms, API marketplaces, enterprise app stores, or partner ecosystems—where you successfully curated supply and drove buyer demand.
Direct experience designing productized commercial mechanics, including meter-based consumption, usage/outcome pricing, committed-spend drawdowns, and multi-sided revenue distribution.
Hands-on familiarity with modern AI agent stacks (MCP, agent-to-agent protocols, tool calling, semantic layers, and non-human identity/delegation mechanisms) to engage credibly with enterprise architects and developer teams.
Ability to navigate extreme ambiguity, define new product categories, and execute hypothesis-driven roadmaps without relying on existing templates.
Experience in cloud marketplaces, AI platform ecosystems, developer tools, or enterprise SaaS ecosystems (e.g., major cloud platforms, AI-native infrastructure vendors, or developer infrastructure companies).