As a Product Designer at Maze, you'll define what product design looks like for AI agents in cybersecurity — a problem space where the design patterns don't exist yet. This is an early-hire role at a well-funded Series A startup building at the intersection of generative AI and security, and you'll own the product surface end-to-end while working directly with our Head of Product, engineering, and founders
The product challenge is genuinely new. Our AI agents investigate vulnerabilities autonomously, surface findings with real context, and collaborate with security teams to cut through noise. Your job is to design how humans and agents work together — how trust gets built, how decisions get communicated, how complex security workflows become understandable. There's no playbook for this. You'll create one
This role suits someone who operates closer to a product director than a screen-shipper — driving direction, influencing strategy, and making business-impact calls, alongside the visual craft to deliver them. You'll be using AI tools daily to move faster, but your craft is the floor: every design choice should hold up on its own merits, independent of how it was generated. Success looks like a design system shipped and adopted across the product, and concrete product outcomes — feature adoption, POC-to-customer conversion, and customer satisfaction with the experiences you ship
Visual Craft for Data-Dense UI: A portfolio that holds up to detailed scrutiny — strong colour theory, deliberate visual hierarchy, considered information architecture for complex workflows. This is the bar, not a nice-to-have. Your interview will dig into specific design choices and why you made them
Product Design Track Record: 4-7 years of professional product design experience, with shipped work in B2B SaaS. We're flexible on years; demonstrated craft and clear ownership matter more than time served
Data-Heavy B2B Interfaces: Direct experience designing for complex workflows, dense data, and technical audiences. Dashboards, investigation tools, developer products, security platforms — the kind of UI where information density and decision support actually matter
AI as Tool, Not Crutch: You use AI tools (Figma AI, Cursor, v0, Midjourney, ChatGPT/Claude, etc.) as part of your daily workflow and can speak credibly to what they're good for and where they break down. Critically, every design choice you ship should hold up on its own — AI accelerates your work, it doesn't substitute for foundational craft
Product-Strategic Thinking: Track record of driving product direction, not just executing on briefs. You've influenced what to build with research, framed problems for leadership, and made business-impact calls — ideally in environments where you operated without a dedicated PM
Deep Engineering Collaboration: Demonstrable history of shipping work in tight partnership with engineers — including backend. Pairing on implementation, working in design tokens, understanding the systems your designs land in, building consensus rather than shipping around resistance
Design Systems Experience: Background building or meaningfully contributing to a design system in a production product. You think in components, tokens, and patterns, not one-off screens
Customer-Led Approach: Comfortable running discovery directly with users, synthesising what you hear, and using that to make calls about what to build. You don't wait for research to be handed to you