Marketplace & PLG - AI-Native Senior Product Manager

Job Description

This role is connective tissue between product and commercial outcomes - you'll partner directly with multiple functions including Sales, CS, and Marketing as peers, translating GTM data into product priorities.

You will own in-product upsell and cross-sell surfaces spanning a portfolio of products - identifying the moments where expansion is natural, building the flows, and tying them to measurable revenue outcomes.

Enterprise onboarding complexity is core to this role - multi-stakeholder setup flows, provisioning, guided configuration, and integrations across a portfolio of products.

Revenue attribution is a first-class skill here: you will be expected to trace how product changes influence acquisition, activation, and expansion metrics and build business cases accordingly.

Comfort with SaaS pricing models and packaging and how they interact with onboarding and growth is expected.

• Use AI tools as core infrastructure in your daily work, not as novelties, but as force multipliers for research, analysis, communication, and decision-making, including:
  • Compress discovery and validation cycles by using AI to synthesize customer feedback, analyze competitive landscapes, and generate first-draft artifacts (PRDs, specs, mockups) that you then refine with product judgment.
  • Architect your own analysis pipelines: use AI to query and synthesize large datasets, extract patterns from user interviews, and surface insights that would otherwise require weeks of manual effort.
  • Continuously evolve your AI toolkit and share effective patterns with the broader product organization.
  • Prototype and validate product concepts rapidly. Arrive at planning discussions with working proofs-of-concept, not just slide decks.
  • Maintain deep fluency in the AI product landscape: what competitors are building, what customers are adopting, and where the technology is heading.
• Own and communicate the strategic roadmap for your assigned product area. Identify where AI creates transformative value versus incremental improvement, and prioritize accordingly.
• Think architecturally: build capabilities that solve multiple problems and expand the product's surface area, rather than addressing isolated requests.
• Translate quantified customer signals (revenue impact, churn risk, deal blockers) into product decisions that go beyond feature requests.
• Lead the full product lifecycle: discovery, definition, development, evaluation, launch, and iteration. Own execution with engineering teams. Partner with GTM teams to ensure product capabilities are positioned, launched, and adopted.
• Ship iteratively: establish feedback loops with real users early and often, and use data to inform the next cycle.
• Other duties as assigned.

• Bachelor's degree or equivalent work experience.
• 5+ years of product management experience in a software/SaaS environment.
• Demonstrated, meaningful use of AI tools in your own PM workflow. You should be able to speak concretely to how AI has changed the way you work, what it's replaced, and where you've found its limits.
• Experience building or shipping product capabilities that incorporate AI/ML, with at least one production deployment preferred.
• Experience working with engineering teams on AI/ML systems (model integration, context engineering, evaluation pipelines, data quality).

• Working understanding of foundation models, their capabilities, limitations, and appropriate use cases.
• Familiarity with AI product patterns: RAG, agentic workflows, embeddings, fine‑tuning, and evaluation frameworks.
• Understanding of APIs, cloud infrastructure, data pipelines, and modern development practices.
• Comfort using AI‑assisted development and prototyping tools (e.g., Claude, Cursor, or similar) to validate concepts and accelerate decision‑making.
• Revenue fluency: ability to read customer signals as product priorities with dollar values attached, including churn risk, deal blockers, and expansion opportunities.
• Strong analytical skills with experience using data to drive prioritization, measure outcomes, and build business cases.
• Excellent written and verbal communication, with the ability to produce clear product specs, strategy…