Highbeam

Highbeam

Senior Product Manager

New York · Senior

Sponsorship not specifiedDetected 69 days ago
LLMsAgentic AIExcelShopify

About the role

  • The bar is a meaningful product shipped fast, with adoption and monetization to match.
  • This role is based in our NoHo, NYC office.

Responsibilities

  • Own the Intelligence product surface across banking, bill pay, cards, and treasury
  • Drive weekly product velocity: specs → build → QA → launch
  • Own 0→1 product definition in ambiguous areas
  • Drive adoption and monetization, not just launches: ensure workflows are actually used
  • Highbeam is building the future of business banking and cash management.

Requirements

  • 4-6 years PM experience

Nice to have

  • You love working in-person with a high-performing team
  • You enjoy working in an idea-meritocratic, low-ego environment
  • You are proactive and self-directed, and you excel in ambiguous, fast moving environments
  • You care about delivering a polished customer experience
  • Chance to join the founding team of a well-funded startup chasing a huge opportunity

Skills

  • Improve speed of iteration across product (faster cycles, tighter feedback loops)
  • Contribute to product narrative + positioning
  • Highbeam becomes known for AI-native financial workflows, not just banking
  • Faster shipping of meaningful product (not incremental features)
  • Measurable lift in product adoption (bill pay, cards, treasury)
  • 4-6 years PM experience; early-stage operator (PM #1-5 at Series A-C)
  • Comfortable with AI tools for iteration and product validation
  • Has built AI/LLM products as the core experience

Compensation

  • Competitive salary and meaningful equity

Benefits

  • Competitive salary and meaningful equity
  • Comprehensive health & benefits package
  • Stipends for lunch, commute, wellness, and purchasing customer products
  • We've raised $42M in equity from Acrew, FirstMark, Mayfield, and Two Sigma Ventures.

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