Who you are

- 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 robust 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

- 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





What the job involves

- 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

- 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

The application 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

📌 Senior Product Designer (Toronto)
🏢 Docebo
📍 Toronto