Staff Product Designer

About SecurityScorecard:

SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint.

Headquartered in New York City, our culture has been recognized by Inc Magazine as a “Best Workplace,” by Crain’s NY as a “Best Places to Work in NYC,” and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital.

About the Role:

We are seeking a highly technical Staff Product Designer to join our Product Design team at SecurityScorecard. In this role, you will design complex AI-powered cyber risk workflows touching on third-party risk assessments, automated security questionnaires, and continuous monitoring. You possess deep expertise in B2B SaaS user experience paradigms, such as dense data, complex permissioning, and multi-tenant workflows. You have deep experience leveraging AI in all phases of your design process, including grounding your prototypes directly in our codebase and design system rather than generating disconnected concepts, and you’re comfortable building and scrapping fast rather than getting attached to a single direction.

What You’ll Do

• Master high-complexity workflows. Own the end-to-end design of deeply technical AI-enabled workflows, including third-party vendor risk assessments, automated security questionnaires, and continuous monitoring.
• Ground decisions in evidence. Run usability tests, synthesize behavioral and product analytics (e.g., FullStory, Pendo), and fold research findings into your design iterations.
• Design for enterprise constraints. Systematically design for complex B2B paradigms, including role-based access control, multi-tenant environments, and complex data-filtering mechanisms, treating these as design material rather than obstacles.
• Bridge design and code with AI prototyping. Work directly against our codebase and design system, using Claude to produce interactive prototypes that are anchored in how our product actually works, not invented from scratch. Communicate design intent through prompting.
• Work AI-native across your design process. Leverage AI to synthesize research, rapidly visualize concepts, explore edge cases, and validate functional prototypes to compress iteration cycles without lowering the craft bar.
• Strengthen our design system. Contribute to our design system to ensure durable patterns and machine readability for AI prototyping at scale, with accessibility as a default (WCAG 2.2).
• Build designer confidence with AI. Raise the product design team’s AI fluency through collaborative prototyping workshops and shared AI prototyping techniques to elevate the team’s collective technical skillsets.
• Partner cross-functionally. Work alongside Product and Engineering to turn ambiguous briefs into defensible solutions, and push back with evidence when the brief is wrong.

Required Qualifications:

• 7+ years of product design experience, with at least 3+ years designing B2B SaaS experiences in a platform environment. B2C design background does not translate to this role.
• A proven portfolio demonstrating strong handling of high-complexity UI challenges, such as multi-dimensional data, analytics dashboarding, permissions management, or deep system nesting, plus a track record of turning ambiguous problems into shipped work without heavy oversight.
• Demonstrated, hands-on use of AI in your own design practice, including prompting AI tooling such as Claude to build interactive prototypes in code that are grounded in an existing codebase and design s…