Senior Product Manager - Streamlit

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Product Management

Senior Product Manager to lead the transition of Streamlit from an open-source library to an enterprise business within Snowflake. The role involves owning the strategy, growth, and P&L for Streamlit in Snowflake, bridging the gap between the open-source community and enterprise customers, and defining how LLMs and agentic workflows integrate with Streamlit.

What you'd actually do

  1. Own the end-to-end strategy for making Streamlit in Snowflake the gold standard for building and running enterprise-grade data applications and AI agents.
  2. Lead the charge and work with Sales, Marketing and Engineering to grow the Streamlit in Snowflake business.
  3. Manage the business outcomes for your area, identifying levers for adoption, retention, and monetization across thousands of enterprise accounts.
  4. Partner with the Cortex AI team to define how LLMs and agentic workflows integrate with Streamlit, enabling users to build using Snowflake’s native AI primitives.
  5. Act as the primary interface between the Open Source Streamlit team and the Snowflake Enterprise team to ensure a cohesive "one-Streamlit" experience.

Skills

Required

  • 5+ years of Product Management experience in B2B SaaS, developer platforms, or cloud infrastructure.
  • Strong understanding of cloud infrastructure and the Python ecosystem.
  • Comfortable discussing technical tradeoffs with senior engineers.
  • Basic proficiency in writing Python code.
  • Proven track record of taking ambitious products to commercial success at scale.
  • High-judgment design skills.
  • Data-driven and comfortable using metrics and AI-assisted analysis to identify growth gaps and prioritize a roadmap under ambiguity.
  • Resilient, low-ego, and thrive in an environment where you are accountable for end-to-end outcomes, good or bad.

Nice to have

  • Prior experience with Streamlit (OS or Enterprise) or similar Python app frameworks (Shiny, Dash).
  • Experience in the AI/ML space, particularly with LLM orchestration or agentic frameworks.
  • Background in Marketplace or Native App ecosystems.
  • Prior experience at a high-growth developer-centric company (e.g., Applications Infrastructure or a major Hyperscaler).

What the JD emphasized

  • P&L
  • enterprise-grade data applications and AI agents
  • growth
  • monetization
  • LLMs and agentic workflows
  • AI primitives
  • Open Source Streamlit team
  • Snowflake Enterprise team
  • Python ecosystem
  • Python code
  • AI/ML space
  • LLM orchestration or agentic frameworks