Pearl Abyss Europe

Pearl Abyss Europe

Director, Product Management

United States · Director

Sponsorship not specifiedDetected 1 day ago
Machine LearningProduct StrategyProject ManagementBusiness DevelopmentResearchAdaptability

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odds of building a lasting career here

25Risky
Cap-exempt (no lottery)0
Sponsors this role35
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • AI is transforming every industry, but enterprise customers need solutions they can trust.

Responsibilities

  • Define the go-to-market strategy. Partner with Business Development to shape the go-to-market strategy, value proposition, competitive positioning, pricing, packaging, and business model.
  • Build and scale enterprise offerings. Define and productize Pearl's AI + Human offerings, determining how they're packaged, delivered, measured, and continuously improved.
  • While you'll set the strategy, you'll also operate as the team's lead Product Manager, working closely with Engineering, Design, Project Management, and GTM partners to ship products, solve customer problems, and drive measurable business outcomes.
  • A business builder. You're excited by the opportunity to own a business, not just a roadmap. You naturally connect customer needs, product strategy, go-to-market, and commercial outcomes into a cohesive plan.
  • We welcome people from all backgrounds who seek the opportunity to help build a future where professional services are readily available to all.
  • Own the business end-to-end.
  • Lead cross-functional execution.

Requirements

  • A proven 0-to-1 builder.
  • You know how to identify the riskiest assumptions, run focused experiments, learn quickly, and determine when to invest, iterate, or pivot.
  • Ability to turn ambiguity into execution.
  • Prior experience as an individual contributor Product Manager is required.
  • Experience in frontier AI, enterprise SaaS, insurance, legal technology, veterinary, or automotive industries.
  • Experience productizing expert networks, human data services, AI evaluation products, or data-labeling services.

Nice to have

  • Enterprise B2B experience.
  • Experience owning a product line, business, or P&L is strongly preferred.

Compensation

  • Pearl will provide pay transparency information upon application to those in qualifying jurisdictions. ( Employment is with JustAnswer LLC, a Pearl company.)

Benefits

  • You'll define the vision, strategy, and goals, and lead a lean cross-functional team through execution and delivery.

Company info

  • Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere.
  • Our Values
  • Data driven: Data decides, not egos
  • Courageous: We take risks and challenge the status quo
  • We're constantly learning, creating, and adapting
  • We focus on customers, using lean testing to learn how to serve them best
  • Past success is not a guarantee of future success
  • Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast.
  • Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere.
  • Innovative: We're constantly learning, creating, and adapting
  • Lean: We focus on customers, using lean testing to learn how to serve them best
  • Humble: Past success is not a guarantee of future success
  • Data driven:
  • Data decides, not egos

Equal opportunity

  • Pearl is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status.

This listing is sourced directly from Pearl Abyss Europe's careers page and normalized into a canonical job model.