Lead AI Product Manager - AI Trust

Monday.com Monday.com · Enterprise · Tel-Aviv, Israel · Product

Lead AI Product Manager for AI Trust at monday.com, focusing on building the trust layer for autonomous AI agents within their work platform. The role involves defining strategy, shipping products that enable organizations to trust and control AI agents, and designing for human-AI interaction and collaboration. This is a 0-to-1 role addressing a novel industry challenge.

What you'd actually do

  1. Co-own strategy with the Group PM and drive one or more core product areas end-to-end.
  2. Build the surfaces and systems that give organizations confidence in AI agents.
  3. Design for new types of relationships between organizations and autonomous agents.
  4. Design for the psychology of trust and how humans and AI work together.
  5. Sit in calls with enterprise accounts navigating internal AI policies, hear their objections firsthand, and turn those blockers into product.

Skills

Required

  • 8+ years of product management experience shipping products
  • Full-stack PM experience: qual research, defined metrics, executed A/B tests, designed user experiences, influenced cross-org stakeholders
  • Creative and fast
  • Thrive in ambiguity
  • Make decisions with 70% of the information
  • Course-correct rather than consensus-seek
  • Strong communicator
  • Frame a problem for leadership
  • Sell a direction to engineering
  • Translate customer pain into product narrative
  • Influence without authority across functions and seniority levels
  • Curious and adaptive
  • Learn new domains quickly
  • Follow where the problem leads
  • Not precious about your first hypothesis

Nice to have

  • Experience designing for human behavior, UX psychology, or high-stakes user decisions
  • Exposure to AI/ML products, platform products, or builder tooling
  • Technical background (CS degree or equivalent depth)
  • Experience with trust, governance, security, compliance product areas (admin tools, permissions, audit, policy engines)

What the JD emphasized

  • building trust between organizations and autonomous AI agents
  • organizations are blocking AI adoption because they lack visibility into what agents do control over what they can access, and confidence that the spend is worth it
  • How does an admin set boundaries for something that acts on its own?
  • How does an agent communicate uncertainty without eroding confidence?
  • How do you calibrate trust gradually - so autonomy expands as the agent proves itself?
  • Trust is built (and broken) in micro-moments: the way an agent explains its reasoning, the way it asks for permission, the way it surfaces a mistake.
  • building trust infrastructure that makes organizations want to give agents more autonomy over time, not less.
  • This is one of the most interesting unsolved problems in enterprise AI right now.
  • nobody's cracked it yet.
  • build something that doesn't exist yet

Other signals

  • AI agents
  • trust layer
  • autonomous AI agents
  • boundaries for agents
  • agent reasoning
  • human-AI collaboration