UX Designer

📍 Job Overview

Job Title: UX Designer

Company: Datatonic

Location: City of Zagreb, Zagreb, Croatia

Job Type: Full-Time

Category: User Experience (UX) Design / Product Design

Date Posted: 2026-06-26

Experience Level: Mid-Level (2-4 years)

Remote Status: Remote (Telecommute)

🚀 Role Summary

• Spearhead the user experience (UX) and user interface (UI) design for cutting-edge AI and data-driven solutions, ensuring human-centric and intuitive interactions.

• Drive the complete design lifecycle, from initial discovery and user research to the delivery of high-fidelity, production-ready interfaces for complex AI applications.

• Lead client-facing workshops and design sprints, translating intricate business requirements and Generative AI capabilities into elegant, actionable design strategies.

• Collaborate closely with Data Scientists, ML Engineers, and Architects to ensure technical feasibility and seamless integration of design with Google Cloud Platform capabilities.

📝 Enhancement Note: While the title is "UX Designer," the responsibilities and required skills, particularly around client engagement, workshop facilitation, and collaboration with technical teams on AI solutions, suggest a role that blends traditional UX/UI with elements of a Product Designer or even a Design Consultant, especially within a fast-paced consultancy environment. The focus on AI and Google Cloud Platform indicates a specialized domain.

📈 Primary Responsibilities

• Lead Discovery & Strategy: Drive the interpretation of complex business challenges and AI capabilities into compelling design strategies and user-centered solutions.

• End-to-End Design Ownership: Conceptualize, design, and maintain design systems, wireframes, user flows, and high-fidelity mockups for AI-powered applications, transforming complex data into accessible user experiences.

• Client Engagement & Workshop Facilitation: Lead and facilitate client discovery workshops, design sprints, and user research sessions to gather requirements, align stakeholders, and validate product concepts.

• User Research & Validation: Plan and execute qualitative and quantitative user research, usability testing, and A/B testing to inform design decisions and iterate on solutions based on performance data and user feedback.

• Cross-Functional Partnership: Collaborate effectively with Data Scientists, Machine Learning Engineers, Architects, and Project Managers to ensure design solutions are technically feasible, aligned with project goals, and leverage Google Cloud Platform capabilities.

• Production-Ready Deliverables: Produce detailed, production-ready design assets, specifications, and documentation, working closely with engineering teams to ensure accurate and high-fidelity implementation.

• Advocacy for Design Excellence: Champion design best practices, accessibility standards, and a user-first approach throughout the product development lifecycle.

📝 Enhancement Note: The emphasis on "Leading Discovery," "Workshop Facilitation," and "Client Engagement" alongside core UX/UI tasks indicates a strong client-facing component. This role requires not just design execution but also the ability to consult and guide clients through the design process for AI solutions.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's degree in Design, Human-Computer Interaction (HCI), Computer Science, or a related field is typically expected for mid-level design roles. A strong portfolio can often substitute for formal education.

Experience: 2–4 years of progressive experience in UX/UI design, with a demonstrated track record of successfully delivering end-to-end design for complex web applications, ideally in enterprise or data-centric environments.

Required Skills:

• Portfolio: A robust portfolio showcasing end-to-end UX/UI design projects for complex web applications, demonstrating problem-solving skills and design process.

• Design Tools: Expert proficiency in modern design and prototyping tools, with a strong emphasis on Figma.

• Design Systems: Proven experience in creating, maintaining, and scaling design systems for consistency and efficiency.

• User Research & Testing: Strong command of qualitative and quantitative user research methodologies, information architecture, usability testing, and rapid prototyping.

• Technical Understanding: Solid understanding of HTML/CSS and familiarity with front-end frameworks (e.g., React, Vue.js) to facilitate effective collaboration with engineering teams.

• Stakeholder Management: Demonstrated ability to confidently present design concepts, rationale, and decisions to diverse audiences, including technical teams and C-suite clients.

• Workshop Facilitation: Experience leading design thinking workshops, discovery sessions, and design sprints.

• AI/ML Curiosity: A keen interest in AI/ML trends and a proactive approach to understanding how these technologies impact user behavior and interface design.

Preferred Skills:

• Hands-on experience designing specifically for Machine Learning (ML) or Generative AI products.

• Familiarity with Google Cloud Platform (GCP) services and interfaces.

• Experience working within a fast-paced scale-up or consultancy environment.

• Knowledge of data visualization best practices.

📝 Enhancement Note: The experience requirement (2-4 years) combined with the expectation to "lead" workshops and "own" the design lifecycle suggests a candidate who is ready to step up and take significant ownership, rather than a purely junior role. The "Bonus Points" are highly relevant to the company's core business.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• End-to-End Case Studies: Showcase at least 2-3 comprehensive case studies demonstrating the full UX/UI design process from problem definition and user research through ideation, wireframing, prototyping, user testing, and final UI design.

• Problem-Solution Framing: Clearly articulate the business problem or user need addressed, the constraints, and how your design solutions effectively solved them.

• Process Documentation: Illustrate your design process, including methodologies used (e.g., user journeys, personas, wireframes, prototypes, usability testing plans and results).

• Tool Proficiency: Highlight your expertise with specific design tools, particularly Figma, and any experience with design systems.

• Impact & Outcomes: Quantify the impact of your designs where possible, using metrics related to user engagement, task completion rates, or business objectives.

Process Documentation:

• Demonstrate an understanding of how to document design processes, including user flows, interaction specifications, and asset handoffs to engineering.

• Showcase experience in creating or contributing to design systems, including component libraries and style guides.

• Provide examples of how user feedback and testing results were incorporated into iterative design improvements.

📝 Enhancement Note: For a role involving client interaction and AI solutions, the portfolio should emphasize not just visual design but also the strategic thinking, user research rigor, and collaborative approach taken to solve complex problems. Demonstrating how designs address technical constraints or leverage AI capabilities will be highly advantageous.

💵 Compensation & Benefits

Salary Range: Based on the provided location (Zagreb, Croatia), experience level (2-4 years), and the nature of a remote role within a tech consultancy, a competitive salary range would likely be between €30,000 - €45,000 per annum. This estimate considers the cost of living in Zagreb, the demand for specialized UX/UI talent in AI, and the typical compensation for remote roles within European tech companies.

Benefits:

• Holiday: 25 days of annual leave plus bank holidays.

• Health & Wellbeing: Private health insurance (Vitality Health) and Smart Health Services, plus 50% gym membership discounts.

• Remote Work Support: A work-from-home allowance to ensure a comfortable and productive remote setup.

• Professional Development: Access to learning platforms like Udemy for continuous skill enhancement.

• Financial Security:

  • Pension scheme with auto-enrollment and employer contributions up to 10% based on service.
  • Life insurance coverage equivalent to 3x base salary.
  • Income protection of up to 75% of base salary for up to 2 years.

• Lifestyle Schemes: Cycle to Work and Tech Scheme participation.

Working Hours: The standard working hours are approximately 40 hours per week. While the role is remote, flexibility may be available, though adherence to project deadlines and client meeting schedules will be essential.

📝 Enhancement Note: The salary range is an estimate based on common market data for UX Designers in Croatia with 2-4 years of experience, considering the company's sector (AI/Consulting) and the remote nature. Benefits are comprehensive and reflect a strong commitment to employee well-being and professional growth.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology Consulting, Artificial Intelligence, Machine Learning, Data Analytics, Google Cloud Platform Partner. Datatonic operates at the intersection of AI innovation and business transformation, helping clients leverage advanced data and ML capabilities.

Company Size: Datatonic is described as a "scale-up" environment, suggesting a dynamic, growing company that likely balances the structure needed for client delivery with the agility and innovation of a startup. The company size is likely in the range of 50-250 employees, based on the "scale-up" descriptor and the comprehensive benefits package.

Founded: Founded in 2017, Datatonic has established itself as a leading AI consultancy, particularly as a premier partner for Google Cloud. This history indicates a company that has successfully navigated early growth and is now focused on scaling its expertise and client impact.

Team Structure:

• The UX Designer will likely be part of a product or project team, working closely with Data Scientists, ML Engineers, AI Consultants, and Project Managers.

• There may be a dedicated design team or a distributed design function within project teams, fostering cross-functional collaboration.

• Reporting is likely to a Design Lead, Head of Product, or a Project/Program Manager, depending on the team's organizational structure. Methodology:

• Datatonic's approach is driven by client success and leveraging Google Cloud's AI/ML capabilities. This implies a methodology focused on agile development, data-driven decision-making, and a strong emphasis on delivering tangible business value.

• Expect a process that prioritizes understanding client needs, rapid prototyping, iterative development, and continuous learning in the rapidly evolving AI landscape.

• Collaboration with clients and internal technical experts is fundamental to their methodology.

Company Website: https://datatonic.com/

📝 Enhancement Note: The company's focus as a Google Cloud AI partner and a "scale-up" suggests an environment that values cutting-edge technology, client success, and rapid professional growth. The UX Designer will be crucial in making these complex technologies accessible and valuable to clients.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a Mid-Level UX Designer (2-4 years of experience). It requires independent work on design projects, leadership in client workshops, and significant collaboration with technical teams. The candidate is expected to own parts of the design lifecycle and contribute strategically.

Reporting Structure: The UX Designer will likely report to a Design Lead, Head of Design, or a Project Manager within a specific client engagement. They will work collaboratively within multi-disciplinary project teams comprising Data Scientists, ML Engineers, and other technical experts.

Operations Impact: The UX Designer's impact is critical in bridging the gap between complex AI/ML capabilities and user understanding. By creating intuitive interfaces and seamless user experiences, they directly influence:

• Client Adoption: Enabling clients to effectively use and benefit from AI-powered solutions.

• Data Utilization: Ensuring that insights derived from data and ML are easily accessible and actionable.

• Project Success: Contributing to the overall success of AI transformation projects by ensuring user needs are met.

• Product Value: Directly shaping the usability and perceived value of Datatonic's AI solutions for clients.

Growth Opportunities:

• Specialization: Deepen expertise in designing for AI, Generative AI, or specific industry verticals where Datatonic operates.

• Leadership: Progress to Senior UX Designer, Lead UX Designer, or Product Design Lead roles, taking on more complex projects and mentoring junior designers.

• Consulting Acumen: Develop stronger client management, workshop facilitation, and strategic consulting skills, potentially moving into roles with a greater business advisory focus.

• Technical Acumen: Enhance understanding of ML, data engineering, and GCP to facilitate even more effective design solutions.

• Cross-Functional Mobility: Potential to transition into Product Management or related roles overseeing AI product development.

📝 Enhancement Note: The "scale-up" nature of Datatonic, combined with a focus on AI and consultancy, offers significant opportunities for rapid career progression and skill development. The role is designed for someone looking to grow their design leadership and technical domain expertise.

🌐 Work Environment

Office Type: The role is designated as "TELECOMMUTE" and "Remote," indicating a fully remote work arrangement. Datatonic supports a hybrid model with a WFH allowance, suggesting flexibility for remote employees to create an optimal home office setup.

Office Location(s): While the job is posted for Zagreb, Croatia, and the remote status means employees can work from their chosen location, Datatonic's primary operations are likely centered around their headquarters and client locations. The company has offices in London and other locations, suggesting a distributed international team.

Workspace Context:

• Remote Collaboration: Expect a highly collaborative remote environment, relying heavily on digital tools for communication, design handoffs, and team syncs.

• Technology Stack: Access to industry-standard design tools (Figma), collaboration platforms (e.g., Slack, Zoom, Google Workspace), and project management software.

• Team Interaction: Regular virtual meetings, team stand-ups, design critiques, and client calls will be integral to the daily workflow. Opportunities for in-person gatherings or team offsites might exist but are not guaranteed for a fully remote role.

Work Schedule: The standard working hours are approximately 40 hours per week. As a remote role serving clients, there might be a need for some flexibility to accommodate different time zones for client meetings or urgent project needs.

📝 Enhancement Note: The remote nature is a key feature. Candidates should be comfortable and effective working independently, with strong self-management skills, and adept at using digital collaboration tools. The WFH allowance acknowledges the importance of a dedicated and comfortable remote workspace.

📄 Application & Portfolio Review Process

Interview Process: Datatonic's interview process for a UX Designer role typically involves several stages designed to assess design skills, technical understanding, problem-solving abilities, and cultural fit.

• Initial Screening: A review of your application, resume, and portfolio to assess basic qualifications and experience.

• Hiring Manager Interview: A conversation to discuss your background, motivations, and understanding of the role, company, and industry.

• Design Challenge/Portfolio Review: This is a crucial stage. You may be asked to present your portfolio in detail, walking through 1-2 case studies. Alternatively, a take-home design challenge or a live design exercise might be assigned to evaluate your design process, problem-solving approach, and tool proficiency.

• Technical/Team Interview: A discussion with potential team members (e.g., Data Scientists, ML Engineers) to assess your technical literacy, collaboration skills, and ability to integrate design with AI/ML concepts.

• Final Interview: Potentially with a senior leader to discuss cultural fit, career aspirations, and alignment with Datatonic's vision.

Portfolio Review Tips:

• Tell a Story: For each case study, clearly articulate the problem, your role, the process you followed, the challenges you faced, your design decisions, and the outcome.

• Show, Don't Just Tell: Use visuals (wireframes, mockups, prototypes, user flows) to illustrate your process and final designs.

• Highlight AI/Data Context: If possible, include projects that demonstrate your ability to design for data-heavy applications or AI/ML interfaces. Explain how you approached the unique challenges of these domains.

• Focus on Figma: Since Figma is a key requirement, be prepared to discuss your workflow, any custom components you've built, and how you leverage its features for collaboration and prototyping.

• Quantify Impact: Whenever possible, use metrics to demonstrate the success of your designs.

• Be Prepared for Questions: Anticipate questions about your design rationale, how you handle feedback, what you would do differently, and your understanding of AI's impact on UX.

Challenge Preparation:

• Understand the Context: If given a design challenge, thoroughly understand the problem statement, target users, and business objectives.

• Embrace Ambiguity: AI and data problems often involve ambiguity. Show your process for navigating this, making assumptions, and seeking clarification.

• Focus on Process: Even if you don't complete a full design, clearly articulate your thought process, the steps you would take, and the rationale behind your decisions.

• Technical Feasibility: Consider the technical constraints, especially in an AI/ML context, and how that might influence your design choices.

📝 Enhancement Note: The emphasis on AI and client engagement means interviewers will be looking for more than just aesthetic design skills. They'll want to see a strategic thinker who can translate complex technical concepts into user-friendly solutions and effectively communicate with diverse stakeholders.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: Expert proficiency is mandatory for wireframing, prototyping, UI design, and design system management.

• Design System Tools: Experience with tools or methodologies for building and maintaining scalable design systems (likely integrated within Figma).

• Prototyping Tools: Proficiency in Figma's prototyping capabilities, or potentially other tools like InVision, Axure, or Adobe XD.

• Collaboration Platforms: Slack for real-time communication, Zoom/Google Meet for video conferencing and client calls.

Analytics & Reporting:

• While not a direct responsibility, familiarity with how user data and analytics inform design decisions is valuable. Experience with tools like Google Analytics, Mixpanel, or Amplitude, and how to interpret user behavior data, would be a plus. CRM & Automation:

• Not directly within the UX Designer's primary scope, but understanding how user data is managed within CRMs (like Salesforce) or how automation impacts user workflows can provide valuable context for designing enterprise solutions. AI/ML Specific Tools:

• Familiarity with tools or platforms used by Data Scientists and ML Engineers (e.g., Jupyter Notebooks, Google Cloud AI Platform services) can aid in cross-functional collaboration.

📝 Enhancement Note: Figma is highlighted as a core requirement. Candidates should be ready to demonstrate advanced usage, including component libraries, auto layout, and interactive prototyping. Understanding the broader tech stack, especially Google Cloud Platform and AI/ML tools, will be beneficial for collaboration.

👥 Team Culture & Values

Operations Values:

• Innovation & Excellence: A drive to push boundaries in AI and data science, delivering high-quality, innovative solutions.

• Client-Centricity: A strong focus on understanding and exceeding client expectations, ensuring their success through AI transformation.

• Collaboration: A belief in the power of teamwork, fostering open communication and mutual support across diverse technical disciplines.

• Data-Driven: A commitment to leveraging data and analytics to inform decisions, measure impact, and drive continuous improvement.

• Learning & Growth: Encouraging continuous learning, skill development, and staying at the forefront of AI and technology trends.

Collaboration Style:

• Cross-Functional Integration: Expect close collaboration with technical teams (Data Scientists, ML Engineers), requiring clear communication and mutual respect for different expertise.

• Agile & Iterative: A working style that embraces agile methodologies, allowing for flexibility, rapid iteration, and continuous feedback loops.

• Knowledge Sharing: A culture that encourages sharing insights, best practices, and learnings across projects and teams.

• Proactive Communication: Emphasis on clear, concise, and proactive communication, especially in a remote setting, to keep all stakeholders informed and aligned.

📝 Enhancement Note: Datatonic values a blend of technical prowess, client focus, and collaborative spirit. The UX Designer will be expected to embody these values by contributing to a positive team dynamic, advocating for users, and driving successful client outcomes through effective design.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for Complexity: Translating highly complex AI/ML concepts and large datasets into intuitive and understandable user experiences for non-technical users.

• Navigating Ambiguity: Working with cutting-edge AI technologies where user interaction patterns may still be evolving, requiring creative problem-solving and hypothesis-driven design.

• Cross-Disciplinary Collaboration: Effectively communicating design rationale and user needs to Data Scientists and ML Engineers who may have different priorities and technical perspectives.

• Client Management: Managing diverse stakeholder expectations and advocating for user-centered design principles within client organizations that may have varying levels of design maturity.

• Remote Work Dynamics: Maintaining strong team cohesion and effective collaboration in a fully remote environment.

Learning & Development Opportunities:

• AI/ML Specialization: Gain deep insights and practical experience in designing for AI, Machine Learning, and Generative AI applications, becoming a specialist in this niche.

• Google Cloud Platform Expertise: Develop familiarity and understanding of GCP's AI and data services, enhancing your ability to design within that ecosystem.

• Consulting Skills: Hone client-facing skills, workshop facilitation techniques, and strategic thinking through direct client engagement.

• Design System Mastery: Further develop expertise in creating and managing robust, scalable design systems.

• Industry Exposure: Work on diverse projects across various industries, broadening your understanding of different business challenges and data applications.

📝 Enhancement Note: The challenges presented are inherent to working at the forefront of AI and in a consultancy model. Datatonic's commitment to learning and growth provides the support structure to overcome these challenges and turn them into significant career development opportunities.

💡 Interview Preparation

Strategy Questions:

• Design Process for AI: "Describe your process for designing a user interface for an AI-powered analytics tool. How would you ensure it's both powerful and easy to use?" (Focus on user research, iterative design, handling complex data visualization, and stakeholder alignment.)

• Client Workshop Approach: "You're tasked with leading a discovery workshop with a client who has a vague idea about using AI for their business. How would you structure this workshop to uncover their needs and define potential solutions?" (Highlight facilitation techniques, active listening, requirement gathering strategies, and managing expectations.)

• Technical Collaboration: "How do you ensure your designs are technically feasible when working with Data Scientists and ML Engineers? Can you give an example of a time you had to compromise or iterate on a design for technical reasons?" (Emphasize communication, understanding technical constraints, and finding collaborative solutions.)

Company & Culture Questions:

• "What interests you about Datatonic and our focus on AI and Google Cloud Platform?" (Research Datatonic's projects, values, and their position in the market.)

• "How do you approach learning about new AI trends and how they might impact user experience?" (Show curiosity and a proactive approach to staying current.)

• "Describe your ideal team environment, especially in a remote setting." (Align your response with Datatonic's collaborative and growth-oriented culture.) Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly define the problem, your role, the process, the challenges, your design decisions (and why), and the final outcome/impact.

• Emphasize Figma Usage: Be ready to demonstrate how you use Figma for wireframing, prototyping, component creation, and collaboration. If you have experience with design systems, highlight that.

• Showcase AI/Data Design: If you have relevant projects, be prepared to discuss the specific challenges of designing for AI or data-intensive applications and how you addressed them.

• Engage Your Audience: Treat the portfolio review as a conversation. Be open to questions and ready to elaborate on your design thinking.

• Prepare for Live Exercises: If a design challenge is part of the process, practice thinking aloud, sketching initial ideas, and outlining your approach to problem-solving under time pressure.

📝 Enhancement Note: Interviewers will be looking for a blend of strong UX fundamentals, practical design execution skills (especially in Figma), a keen interest in AI, and the ability to work effectively with technical teams and clients in a remote consultancy setting.

📌 Application Steps

To apply for this UX Designer position:

• Submit your application through the provided link on Ashby.

• Portfolio Customization: Tailor your portfolio to highlight relevant UX/UI design projects, especially any that involve complex applications, data visualization, or AI/ML concepts. Ensure your Figma expertise is evident.

• Resume Optimization: Clearly articulate your 2-4 years of experience, emphasizing end-to-end design ownership, client interaction, workshop facilitation, and collaboration with technical teams. Use keywords from the job description like "Figma," "Design Systems," "User Research," and "AI."

• Interview Preparation: Practice articulating your design process, preparing to walk through 1-2 key case studies in detail, and brushing up on your understanding of AI's impact on UX.

• Company Research: Thoroughly research Datatonic, their work with Google Cloud, and their position as an AI consultancy. Understand their values and what makes them a unique place to work.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.