Staff Product Designer, AI
Software Engineering, Product, Design, Data Science · Full-time
Contentsquare works with 3,000+ enterprise and mid-market brands on data from 1.3 million websites. We've raised $1.4bn to build the platform, and G2 rates us a Leader across ten enterprise categories. Sense is our agentic layer on top of that: ten years of cross-customer behavioural data, an AI analyst, a chat and visual-stories interface, and a memory and object model underneath both.
This role leads design for Sense's core AI surfaces as a product in its own right, not a feature downstream of someone else's roadmap. That means owning strategy and vision for this surface, not just shipping against a brief. Most of what you're designing here has no reference pattern to draw from yet; part of the job is defining and sharing these patterns.
What you'll do
Own design for Sense Analyst, the object model, and the inline visualisations it returns, from problem framing through to shipped detail.
Lead the experience strategy and vision for this product surface, and shape its roadmap alongside Product Management.
Work from the data model up: what counts as a persistent object, how memory and context carry across sessions, and how that surfaces to the person using it.
Set the quality bar for AI-generated output on these surfaces: what "trustworthy" and "good" look like, and how that gets versioned and evaluated with engineering.
Partner with engineering on customer facing agentic workflows and how AI-generated output gets versioned and trusted.
Work alongside the other designers building the AI-native parts of the product: review each other's work, push each other's thinking, and help less-senior designers on the team build judgement in this space.
What You'll Bring
Staff-level product design experience, most of it in B2B SaaS ideally analytics or workflow tools where users make decisions from complex information.
Hands-on design experience shipping AI or agentic features yourself: chat interfaces, generative output, memory or personalization, human-AI trust patterns.
Ability to reason about the data model underneath an interface
An extensive track record of shipping zero-to-one work in ambiguous problem spaces, with a clear line from that work to business outcomes, not just user outcomes.
Strong collaboration and facilitation skills :you can bring engineering, PM, and other designers to a shared decision, not just present finished work.
Leadership and influence.
Experience designing for LLM and AI experiences, including prompt engineering.
Designing for enterprise or executive personas.
Prototyping in code to test an interaction model before it's built.
A background in analytics, attribution, or behavioural data products.
Nice to have: