TM

Role intelligence

Senior Product Manager — AI Commerce

Hiring manager
Taylor Morgan
Recruiting partner
Dana Whitfield
Department
Product
Location
San Francisco · Hybrid (2 days/week)
Compensation band
$185,000 – $225,000 + equity
Hiring status
Final decisions

Business problem this role solves

Meridian's merchants abandon 38% of AI-assisted checkout setups before launch. This role owns turning our AI commerce assistant from a promising beta into a product merchants trust with revenue.

First 90-day success expectations

  1. Days 1–30: Meet 15+ merchants, audit the beta funnel, align on success metrics
  2. Days 31–60: Ship a prioritized roadmap and one measurable onboarding experiment
  3. Days 61–90: Lead the GA readiness review with engineering, design and GTM

What great looks like

Evaluation scale: 1 No evidence · 2 Limited evidence · 3 Clear evidence · 4 Strong evidence

Product judgment

Critical

Chooses the right problems and makes sound tradeoffs with incomplete information.

Observable evidence: Explains a past prioritization call, the alternatives considered, and what they'd change.

Interview owner: Taylor Morgan, Morgan Chen, Casey Williams

Cross-functional leadership

Critical

Aligns engineering, design and GTM without formal authority.

Observable evidence: Describes resolving a real disagreement and how the team moved forward.

Interview owner: Jamie Park, Morgan Chen

Technical AI/ML fluency

Important

Understands model capabilities, limits and evaluation well enough to make product calls.

Observable evidence: Can reason about precision/recall tradeoffs and failure modes in a product context.

Interview owner: Jamie Park

Execution and experimentation

Critical

Owns delivery end-to-end and designs experiments that change decisions.

Observable evidence: Walks through a launch they drove, including slips, recovery and measured outcomes.

Interview owner: Unassigned

Strategic communication

Important

Writes and speaks with clarity for different audiences.

Observable evidence: Summarizes a complex decision crisply; adapts depth for executives vs. engineers.

Interview owner: Taylor Morgan