- Menlo Security is expanding data-centric protection across its browser security platform — covering DLP, file inspection and sanitization, sensitive data classification, and secure file handling workflows.
- We are hiring a Product Designer to own the end-to-end user experience for this vertical, partnering closely with product management and engineering to design admin-facing policy controls, end-user file interaction flows, and risk and incident surfaces that make complex data protection decisions feel simple and trustworthy
- This is a high-ownership role on a small, tightly connected design team where one person’s work shapes an entire product area.
- Much of what you design sits on top of AI/ML-driven classification and detection, so you will be defining how automated decisions are explained, trusted, and overridden by the people who depend on them.
- Our design team also uses AI-assisted research synthesis and prototyping tools to move from customer signal to testable concept faster, and we expect this role to help set that practice
- Own the design quality and usability of Menlo’s data security and file security surfaces end to end — from admin policy configuration through end-user file interactions and incident remediation
- Make complex, rules-based data protection decisions understandable and actionable for the security admins and end users who rely on them
- Own end-to-end design for data security and file security features: DLP policy configuration, file scanning and sanitization flows, sensitive data detection alerts, and quarantine and remediation workflows
- Translate complex security and compliance logic — data classification rules, file-type policies, content inspection results — into admin experiences that are configurable without being overwhelming
- Design the interaction patterns that make AI/ML-driven classification and detection legible to users: confidence and risk indicators, explanations for why a file was flagged, and clear paths to review, override, or appeal an automated decision
- Design end-user-facing moments — file download warnings, redaction previews, access requests — that balance security friction with productivity
- Partner with product management and engineering to scope features, run discovery with customers and admins, and iterate through delivery, using AI-assisted tools to synthesize interview transcripts, support tickets, and usability sessions into prioritized insight
- Extend the design system with security-specific patterns (risk indicators, policy builders, data flow visualizations), using AI-assisted prototyping and design tooling to explore and test variations quickly before committing to a direction
- Mentor designers on the team and contribute to team-wide craft and process standards, including how the team adopts AI tools responsibly in its workflow
- Success Metrics / KPIs;
- Reduced admin time-to-configure for DLP and file security policies
- Decreased support tickets related to policy setup confusion or false positives
- Increased design system component reuse across data security surfaces
- Positive usability benchmarks from admin console testing
- Strong cross-functional alignment scores from product and engineering partners, per the team’s existing competency framework cadence
4+ years of product design experience, including B2B or enterprise application audiencesProficiency in Figma and modern design system workflowsWorking fluency with AI-assisted design and research tools — for example, using LLM-based tools to synthesize qualitative research or accelerate prototyping — with the judgment to validate outputs before they inform design decisionsExperience designing for technical or admin audiences — policy builders, rules engines, dashboards, or other configuration-heavy interfacesSystems thinking: able to map multi-step workflows with conditional logic and edge cases, such as policy conflict resolution and exception handlingA portfolio that shows complex, rules-based systems simplified into usable interfacesExperience partnering with product management and engineering in an agile environment, including presenting design rationale to cross-functional and executive stakeholdersFamiliarity with data security or file security concepts: DLP, content inspection, sensitive data classificationKnowledge of AI/ML-driven products or AI security — for example, prompt injection risk, AI-assisted threat detection, or model governanceExperience mentoring or growing other designers