Lead AI Product Manager - AI Trust

We are monday.com, a global AI-driven work platform used by 250,000+ customers to reimagine how teams build operational processes, execute work, and create custom business solutions at scale. Our product suite has evolved into an AI-first Work Platform - bringing autonomous agents deeply into workflows, business processes, and enterprise operations. 

As AI agents become core collaborators inside organizations, a fundamental new challenge emerges: how do you trust them?

AI Trust is the group tackling this. We sit within the Agentic Layer of the AI Work Platform, building the trust layer that lets organizations move AI from experiment to real impact - safely, transparently, and at scale.

As PM Lead for AI Trust, you'll co-own strategy with the Group PM and drive one or more core product areas end-to-end. This is a 0-to-1 role at the cutting edge of a problem the industry hasn't standardized yet: building trust between organizations and autonomous AI agents.

Build the product that turns “No” into “Yes”

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. You'll build the surfaces and systems that give them that confidence.

Design for new types of relationships

Agents aren't features - they're autonomous actors inside an organization. The product challenges here are genuinely novel: 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?

Shape how humans and AI work together

This isn't just about admin controls. 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. You'll design for the psychology of trust - the signals that make a person feel safe enough to let go, and the ones that make them pull back.

Work directly with the customers saying "not yet”

This is one of the most customer-facing PM roles at monday. You'll sit in calls with enterprise accounts navigating internal AI policies, hear their objections firsthand, and turn those blockers into product.

Balance enablement with control

The easy version of this role is building restrictions. The hard version - our version - is building trust infrastructure that makes organizations want to give agents more autonomy over time, not less.

• 8+ years of product management experience shipping products across different domains or business models.
• Full-stack PM in the truest sense: you've personally run qual research, defined metrics, executed A/B tests, designed user experiences, and influenced cross-org stakeholders.
• Creative and fast. You thrive in ambiguity, don't over-structure before you move, and make decisions with 70% of the information. You course-correct rather than consensus-seek.
• A strong communicator. You can frame a problem for leadership, sell a direction to engineering, and translate customer pain into product narrative. You influence without authority across functions and seniority levels.
• Curious and adaptive. You learn new domains quickly, follow where the problem leads, and aren't 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).

Why This Role Matters

This is one of the most interesting unsolved problems in enterprise AI right now. Every platform company is racing to figure out how organizations can trust autonomous agents - and nobody's cracked it yet.

You'll work at the intersection of AI, enterprise, and human behavior - building for the people who need to feel confident enough to let agents act. What you ship directly determines whether organizations adopt AI at scale or keep it locked down.

If you want a well-scoped problem with an established playbook - this isn't it. If you want to define a category and build something that doesn't exist yet - let's talk.