# Product Manager

**Company:** [Airtable](https://hotfix.jobs/companies/airtable)
**Location:** San Francisco, CA, New York, NY
**Role:** Product Management
**Salary:** $187k – $235k/yr
**Experience:** 5+ years
**Skills:** Product Management, AI, LLMs, Retrieval, Evals, Prompt Design, Prototyping, Measurement Frameworks
**Posted:** 2026-07-14

> Own end-to-end AI-native product experiences at Airtable, focusing on how humans and AI agents collaborate on structured data and workflows. Requires 5+ years PM experience, deep AI fluency, high agency, and strong product taste for building trustworthy AI interactions.

## Job Description

## What you'll do

- Own a product area end-to-end — from problem discovery through shipped, measured outcomes. Take ideas from ideation all the way to production.
- Build AI-native product experiences — decide how agents and AI capabilities show up in your area, where humans stay in the loop, and how the product earns users' trust.
- Take on systems and structural work — the deeper product problems that cut across surfaces, not just feature iteration.
- Work in prototypes, not just PRDs — use AI tools to build working versions of your ideas and put them in front of people early.
- Define success for outcomes that are inherently fuzzy — build measurement frameworks for AI quality, adoption, and behavior change, and use them to decide what to build next.
- Operate with high agency — identify the most important problems to work on next rather than waiting for scope to be handed to you.

## Who you are

- 5+ years of product management experience, with a track record of shipping products users rely on.
- Genuinely AI-forward. You've automated real work: workflows that synthesize feedback across your product areas, agents that handle parts of your team's job, prototypes instead of documents. The signal we look for is compounding — AI increasingly doing the work for you and your team.
- Technically fluent in AI. You understand how LLMs work, can reason about model capabilities and tradeoffs, and have a point of view on retrieval, evals, and prompt design. You don't need to be an engineer, but you can operate like a team of one inside a modern AI stack.
- High agency; you’re motivated by being handed a hard area, not an execution-oriented roadmap.
- Energized by ambiguity and hard problems. Our priorities shift as the AI landscape shifts; you make progress when a roadmap doesn't exist yet.
- Product taste, especially for AI interactions. You have a refined sense of what makes AI feel helpful rather than frustrating, when to show confidence versus uncertainty, and how transparency builds trust.
- User empathy. You understand how non-technical people think about their data, and you can turn complex capabilities into experiences they trust and use daily.

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