Senior Product Designer, Content Design & Language Systems

Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart : trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. The Adventure Ahead 🚀 As a Senior Product Designer, Content Design & Language Systems , you’ll lead ambiguous product problems where workflow, interaction, information architecture, and language need to work together. You’ll help make Docebo’s complex enterprise experiences clearer, more consistent, and easier to use for admins, creators, managers, and learners. This is not a traditional UX writing role or a localization-operations role. You’ll be a hands-on Product Designer who shapes product behaviour as well as product language. You’ll design complete workflows, build reusable terminology and content patterns, improve AI review and confidence experiences, and embed language guidance into our design system and delivery practices. You’ll shape problems before solutions are fixed, choose appropriate discovery and validation methods, and connect customer evidence, product data, business context, technical constraints, accessibility, and localization risk to clear product decisions. You’ll partner closely with Product Management, Engineering, UX Research, Elemental / Design System, Accessibility, Technical Writing / Localization, AI teams, and other Product Designers—building a shared quality capability without becoming a bottleneck or approval queue. The Day-to-Day 💻 Frame Ambiguous Workflow and Language Problems: Turn incomplete or conflicting inputs into clear problem statements, hypotheses, decision questions, and an actionable path to learning. Lead Discovery and Define Outcomes: Select appropriate research and validation methods; combine customer evidence, product analytics, business context, technical constraints, and localization insight to establish measurable success signals and visible trade-offs. Design Complete Product Workflows: Lead interaction, information-architecture, and content decisions across roles, permissions, states, edge cases, accessibility, responsive behaviour, errors, confirmations, approvals, and recovery. Build Docebo’s Product Language System: Establish terminology, product voice and tone, reusable microcopy patterns, audience guidance, and language principles that improve clarity across product areas. Design Trustworthy AI Moments: Create patterns that help people understand what AI did, what informed it, what needs attention, and how to review, edit, regenerate, approve, reverse, or recover. Embed Guidance into Product Systems: Partner with Elemental / Design System to create component-level guidance, default strings, usage examples, do-and-don’t guidance, and reusable quality checks. Design for Localization Readiness: Own product-side standards for translation-ready writing, terminology reuse, variables and placeholders, language previews, and localization constraints while partnering with Technical Writing / Localization on operational workflows. Prototype and Audit with AI-Assisted Methods: Use appropriate-fidelity prototypes and AI-assisted workflows to explore product behaviour, evaluate alternatives, audit language, and assess usability and technical feasibility before significant implementation investment. Partner Through Shipped Quality: Work closely with Engineering on implementation strategy, design QA, product polish, and post-release iteration using customer feedback and product evidence. Create Reusable Leverage: Turn repeated workflow and language needs into patterns, assets, documentation, terminology, prompts, or practices that improve more than one feature. Mentor and Facilitate: Help designers and cross-functional partners build stronger product-language judgment through critique, decision reviews, workshops, concise documentation, and practical guidance. Your Superpowers 🦸‍♀️ Your portfolio shows ownership of complex, ambiguous workflows or significant product-area work with visible customer and product impact—not only writing samples You can explain how you triangulated qualitative research, quantitative evidence, business risk, localization considerations, and technical constraints You demonstrate strong interaction, visual, information-architecture, content-design, accessibility, and product-language judgment across difficult states and edge cases You have created or contributed to product-language systems, terminology frameworks, component guidance, content pattern libraries, or other reusable product standards You show how prototypes, experiments, audits, or validation changed product direction before or after release You can define meaningful outcomes, distinguish signal from activity, and explain what the team learned after launch You have influenced Product and Engineering decisions early, managed disagreement constructively, and stayed accountable through implementation quality You understand how product language must work across design systems and languages, including translation readiness, terminology reuse, variables, layout constraints, and inclusive communication You use AI-assisted tools thoughtfully for research, synthesis, language exploration, prototyping, quality review, or implementation critique while retaining human judgment and accountability You have helped other designers or cross-functional partners build stronger judgment through mentorship, critique, facilitation, and practical guidance Bonus Points 🌟 Experience designing language and interaction patterns for AI-assisted, agentic, recommendation, conversational, generated-output, or automation workflows Experience with localization tooling and practices such as Lokalise, terminology management, localization previews, translation-quality review, or localization-to-codebase workflows Contributions to design systems, accessibility maturity, product-language systems, research practices, or reusable interaction patterns Experience with enterprise learning, HR technology, content authoring, analytics, knowledge management, administration, or skills platforms Practical experiments with tools such as Codex or similar systems—for AI-assisted audits, product-language linting, prompt packs, prototypes, plugins, scripts, or app-level language guidance—that show you learn by making Our Interview Process 🗺️ Step 1: A 30-minute video call with a member of our Talent team. We’ll get to know you, share more about the role and team, and confirm that we’re aligned. Step 2: A 45–60-minute conversation with the hiring manager focused on your experience, approach, and what interests you about the opportunity. Step 3: A 60-minute portfolio deep dive and collaborative case discussion focused on complex workflow ownership, content and interaction decisions, reusable systems, evidence, craft, and measurable learning or impact. Step 4: A final conversation focused on product-area influence, mentorship, values alignment, and cross-functional decision making. Our Hybrid Work Philosophy 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing.