Meridian Labs · Careers Demo Mode

Senior Product Manager — AI Commerce

Discover what this role is really about.

San Francisco · Hybrid (2 days/week)$185,000 – $225,000 + equityProduct · Hiring manager Taylor Morgan

The real business problem

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.

What you'll do

  • Own the AI Commerce roadmap across checkout, pricing and catalog assistants
  • Partner with ML engineering on evaluation, guardrails and launch criteria
  • Run experiments with merchant design partners and translate learnings into bets
  • Communicate tradeoffs clearly to executives, sales and support

Skills that matter

Product judgment

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

Cross-functional leadership

Aligns engineering, design and GTM without formal authority.

Technical AI/ML fluency

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

Execution and experimentation

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

Strategic communication

Writes and speaks with clarity for different audiences.

Your first 90 days

  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

Within six months, merchant activation on the AI assistant improves meaningfully, the team ships on a predictable cadence, and stakeholders describe product decisions as clear and well-reasoned.

The team

You'll join a pod of 6 engineers, 2 ML engineers, a designer and an analyst. We work in two-week cycles with a weekly product review and a written-first decision culture.

Interview process

  1. 1Recruiter conversation · Dana Whitfield
    Focus: Motivation, logistics, questions
  2. 2Hiring manager interview · Taylor Morgan
    Focus: Product judgment, communication
  3. 3Technical collaboration · Jamie Park
    Focus: AI/ML fluency, working with engineering
  4. 4Design partnership · Morgan Chen
    Focus: Cross-functional leadership
  5. 5Metrics deep-dive · Casey Williams
    Focus: Product judgment with data

Hiring-manager-approved Q&A

Do I need hands-on machine learning experience?

No. You won't train models. You should be comfortable discussing model evaluation, failure modes and tradeoffs with ML engineers, and making product calls based on them.

What will I own in the first 90 days?

You'll audit the beta funnel and meet merchants in month one, ship a prioritized roadmap plus an onboarding experiment in month two, and lead the GA readiness review in month three.

What does success look like?

Within six months: improved merchant activation on the AI assistant, a predictable shipping cadence, and stakeholders who describe product decisions as clear and well-reasoned.

How does the team collaborate?

The pod is 6 engineers, 2 ML engineers, a designer and an analyst. We run two-week cycles, a weekly product review, and a written-first decision culture.

What is the compensation range?

The base salary range is $185,000 – $225,000, plus equity and standard Meridian benefits.

What's still unclear about this role?

This is private and is never used to evaluate your candidacy.