UX Designer

📍 Job Overview

Job Title: UX Designer

Company: Datatonic

Location: Zagreb, Croatia

Job Type: FULL_TIME

Category: UX/UI Design, AI & Data Solutions

Date Posted: 2026-05-29

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

Remote Status: Remote

🚀 Role Summary

• Spearhead the design and delivery of intuitive, user-centric interfaces for cutting-edge AI and Generative AI-powered solutions, ensuring seamless human interaction with complex technologies.

• Drive the entire design lifecycle, from initial discovery and user research to the creation of high-fidelity, production-ready designs and scalable design systems.

• Lead client-facing discovery workshops and design sprints, effectively translating business requirements and technical capabilities into elegant design strategies.

• Collaborate closely with cross-functional teams, including Data Scientists, ML Engineers, and Architects, to ensure design feasibility and alignment with Google Cloud Platform capabilities.

📝 Enhancement Note: This role is positioned as a mid-level UX Designer with a strong emphasis on client interaction and a deep dive into AI/ML applications. The "telecommute" location type combined with the specific country derived indicates a remote position within Croatia, likely with a focus on the Zagreb timezone. The description explicitly mentions leading workshops and directly engaging with clients, suggesting a consultancy or agency-like environment where user experience is a key differentiator for AI solutions.

📈 Primary Responsibilities

• Lead discovery processes to translate complex business requirements and AI capabilities into elegant, user-centric design strategies.

• Own the end-to-end design process, including the creation and maintenance of design systems, wireframes, user flows, and high-fidelity mockups for AI-driven applications.

• Facilitate client-facing workshops and design sprints to gather requirements, align stakeholders, and validate product concepts for AI solutions.

• Plan and execute qualitative and quantitative user research, usability testing, and information architecture to inform design iterations and optimize user experiences.

• Collaborate strategically with Data Scientists, ML Engineers, and Architects to ensure technical feasibility and seamless integration of AI functionalities into user interfaces.

• Deliver production-ready design assets and comprehensive documentation, working closely with engineering teams for accurate, high-fidelity implementation.

• Advocate for design excellence and best practices, ensuring AI-driven applications are accessible, intuitive, and powerful.

📝 Enhancement Note: The responsibilities highlight a blend of hands-on design work, client engagement, and strategic thinking. The emphasis on "AI-powered solutions" and collaboration with "Data Scientists, ML Engineers, and Architects" points to a specialized UX role within a technology-focused company. The expectation to "own the creation and maintenance of design systems" suggests a need for experience in scalable design practices.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a Bachelor's or Master's degree in Human-Computer Interaction, Design, Computer Science, or a related field is often preferred for roles involving complex technical applications and research.

Experience: 2–4 years of dedicated experience in UX/UI design, with a proven track record of delivering end-to-end solutions for complex web applications.

Required Skills:

• Expert proficiency in modern design and prototyping tools, specifically Figma, for creating wireframes, mockups, and interactive prototypes.

• Demonstrated experience in building, maintaining, and scaling design systems to ensure consistency and efficiency across projects.

• Strong understanding of HTML/CSS and how front-end frameworks like React and Vue.js influence design implementation and feasibility.

• Proficient in conducting qualitative and quantitative user research, applying insights to design decisions.

• Skilled in information architecture, rapid prototyping, and user flow mapping for complex applications.

• Excellent stakeholder management capabilities, with the ability to confidently present design decisions to technical teams and C-suite clients.

Preferred Skills:

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

• Familiarity with Google Cloud Platform (GCP) services and their implications for UI/UX design in data-heavy enterprise environments.

• Experience working within a fast-paced scale-up or consultancy setting, adapting to evolving project needs and client demands.

📝 Enhancement Note: The "2-4 years" experience level aligns with a mid-level designer who can take ownership but still benefits from senior guidance. The emphasis on Figma and design systems is standard for modern UX roles. The technical literacy requirement (HTML/CSS, React/Vue.js) is crucial for effective collaboration with engineering teams in a tech-centric company. The "AI Curiosity" is a key differentiator, indicating a forward-thinking approach to the role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• A comprehensive portfolio showcasing successful end-to-end delivery of complex web applications, with a focus on user-centric design and problem-solving.

• Case studies demonstrating your process for translating complex business requirements and technical constraints into intuitive user experiences, particularly for data-intensive or AI-driven products.

• Examples of your work in creating and maintaining scalable design systems, illustrating consistency and efficiency.

• Evidence of your user research and testing methodologies, including how you gathered insights and iterated on designs based on feedback and performance data.

Process Documentation:

• Showcase your approach to leading discovery workshops and design sprints, including how you facilitated stakeholder alignment and validated concepts.

• Detail your methodology for user research and usability testing, explaining how you translated findings into actionable design improvements.

• Illustrate your process for collaborating with technical teams (e.g., Data Scientists, ML Engineers) to ensure design feasibility and effective integration of AI functionalities.

• Provide examples of how you've ensured design consistency and scalability through design systems.

📝 Enhancement Note: For a UX role focused on AI and client interaction, the portfolio needs to clearly articulate the design process, especially how complex technical challenges were addressed through user-centered design. The ability to demonstrate leadership in workshops and collaboration with technical experts will be highly valued.

💵 Compensation & Benefits

Salary Range: Based on the provided location (Zagreb, Croatia), experience level (2-4 years), and industry (AI/Tech Consultancy), a competitive salary range for a UX Designer would typically fall between €25,000 - €45,000 per year gross. This estimate is derived from market research for similar roles in Croatia, considering the specialized nature of AI/ML design and remote work flexibility which can sometimes influence compensation.

Benefits:

• Holiday: 25 days of annual leave plus bank holidays, offering a healthy work-life balance.

• Health Perks: Comprehensive private health insurance through Vitality Health, along with access to Smart Health Services for well-being support.

• Fitness & Wellbeing: A generous 50% discount on gym memberships to encourage an active lifestyle.

• Hybrid Model Support: A Work From Home allowance to ensure a comfortable and productive remote working setup.

• Learning & Growth: Access to extensive learning resources via platforms like Udemy, supporting continuous professional development in UX and AI.

• Pension Scheme: Auto-enrollment with employer contributions that can increase up to 10% based on length of service.

• Life Insurance: A valuable benefit providing 3x your base salary coverage.

• Income Protection: Up to 75% of your base salary for up to 2 years, offering financial security.

• Additional Schemes: Access to Cycle to Work and Tech Schemes, promoting sustainable commuting and access to technology.

Working Hours: Standard full-time working hours are assumed to be 40 hours per week, with flexibility often afforded in remote roles to manage work-life balance effectively, particularly concerning collaboration across different time zones if applicable.

📝 Enhancement Note: The salary range is an estimation based on general market data for UX Designers in Croatia with 2-4 years of experience. The specific salary offered can vary based on the company's compensation strategy, the candidate's specific skills and portfolio, and the precise scope of responsibilities within the Datatonic team. The benefits package is extensive and aligns well with attracting and retaining talent in the tech sector.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, specifically AI & Data Solutions, with a focus on Machine Learning and Google Cloud Platform. Datatonic operates as a premier partner for Google Cloud, indicating a high level of technical expertise and a commitment to cutting-edge solutions.

Company Size: Datatonic is described as a scale-up, suggesting a dynamic, growth-oriented environment. This typically means opportunities for rapid professional development, increased responsibility, and a more agile, less bureaucratic structure compared to larger, established corporations.

Founded: While the founding date is not explicitly provided in the raw data, the mention of "scale-up" implies a company that has moved beyond its startup phase and is actively expanding its operations and client base. This often translates to a culture of innovation and a focus on delivering tangible business value.

Team Structure:

• The UX Designer will likely be part of a product or project team, working closely with Data Scientists, ML Engineers, and Architects, reflecting a highly collaborative, interdisciplinary structure common in AI/ML consultancies.

• Reporting structure might involve a Design Lead or a Project Manager, depending on the team's organization.

Methodology:

• Datatonic's focus on Google Cloud, AI, and data analytics suggests a methodology that is data-driven, leveraging advanced analytics and machine learning techniques.

• Design processes will likely integrate agile principles, rapid prototyping, and continuous feedback loops with clients and technical teams.

• Emphasis on innovation and pushing technological boundaries implies exploration of new AI applications and their user interface implications.

Company Website: https://datatonic.com/

📝 Enhancement Note: The company's positioning as a Google Cloud premier partner and its focus on AI/ML indicate a culture that values deep technical expertise, innovation, and client-focused solutions. A "scale-up" environment suggests a fast-paced, adaptable culture where individual contributions are highly visible and impactful.

📈 Career & Growth Analysis

Operations Career Level: This role is for a Mid-Level UX Designer, typically requiring 2-4 years of experience. It signifies an individual who can independently manage design tasks, lead smaller initiatives, and contribute significantly to project outcomes. They are expected to have a solid grasp of UX principles and tools, and begin to develop expertise in specialized areas like AI design.

Reporting Structure: The UX Designer will likely report to a Design Lead, Head of Design, or potentially a Project Manager overseeing client engagements. They will work closely with Data Scientists, ML Engineers, and Solutions Architects, forming a core project team.

Operations Impact: The UX Designer's impact is critical in translating complex AI and data solutions into user-friendly products that drive client adoption and achieve business objectives. By ensuring intuitive interfaces for AI-powered tools, they directly influence user efficiency, data utilization, and the overall success and ROI of Datatonic's client projects.

Growth Opportunities:

• Specialization: Deepen expertise in designing for AI, Generative AI, and complex data visualization, becoming a go-to specialist in this niche.

• Leadership: Progress to a Senior UX Designer role, leading larger projects, mentoring junior designers, and taking on more strategic design responsibilities, including client-facing leadership.

• Cross-functional Skill Development: Gain deeper understanding of ML, data engineering, and cloud technologies through close collaboration, enhancing ability to design for technical products.

• Client Engagement: Develop advanced client management and workshop facilitation skills, potentially leading to roles with more direct client responsibility or business development aspects.

📝 Enhancement Note: The growth path for a UX Designer in an AI-focused consultancy like Datatonic is strong, moving from independent contributor to specialist or leader. The opportunity to work with cutting-edge AI technologies provides a unique and valuable career trajectory.

🌐 Work Environment

Office Type: This position is designated as "TELECOMMUTE," meaning it is a fully remote role. Datatonic offers a hybrid model approach with a WFH allowance, indicating support for remote employees to establish comfortable and productive home office setups.

Office Location(s): The primary location derived is Zagreb, Croatia. While the role is remote, candidates are expected to be based in Croatia, likely aligning with the company's operational hub and timezone for team collaboration.

Workspace Context:

• The remote setup provides autonomy and flexibility in managing one's workspace and schedule.

• Collaboration will primarily occur through digital tools (e.g., Figma, Slack, video conferencing), requiring effective virtual communication and teamwork.

• Access to learning platforms like Udemy and a WFH allowance contributes to a supportive remote working environment focused on employee well-being and productivity.

• While not physically in an office, the company culture encourages connection through virtual means, fostering a sense of team despite geographical separation.

Work Schedule: Standard full-time hours (estimated 40 hours/week) apply, but the remote nature may offer some flexibility in daily scheduling, provided that collaboration with team members and clients across potentially different time zones is maintained.

📝 Enhancement Note: The "TELECOMMUTE" designation clearly defines this as a remote role. The mention of a "Hybrid Model" and "WFH allowance" implies that while fully remote, the company supports a flexible approach to work, potentially allowing for occasional in-person meetups or hybrid arrangements if the employee is near a company hub. The key is that the role can be performed from anywhere within Croatia.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your application, focusing on your resume and portfolio, to assess experience, skills, and alignment with the role's requirements.

• Portfolio Presentation: A dedicated session where you will present your portfolio, discussing 2-3 key projects that demonstrate your end-to-end UX design process, problem-solving skills, and impact, especially relevant to AI/data applications.

• Technical/Skills Interview: Discussion about your proficiency with design tools (Figma), design systems, user research methodologies, and technical understanding (HTML/CSS, frameworks). You may be asked to walk through specific design challenges or approaches.

• Client Workshop Simulation/Case Study: Potentially a task or discussion simulating a client workshop or a case study analysis, assessing your ability to translate requirements, facilitate discussions, and propose design solutions for complex AI scenarios.

• Team/Cultural Fit Interview: Conversation with potential team members (Data Scientists, Engineers, etc.) to assess collaboration style, communication, and how you'd fit into Datatonic's innovative and client-focused culture.

Portfolio Review Tips:

• Curate Strategically: Select 2-3 projects that best showcase your end-to-end process for complex web applications, ideally including AI/data-related work.

• Tell a Story: For each project, clearly articulate the problem, your role, your process (research, ideation, design, testing), the challenges faced, and the measurable outcomes or impact.

• Highlight AI Relevance: If you have AI/ML design experience, emphasize it. If not, draw parallels to how your experience with complex data or enterprise applications translates to designing for AI.

• Showcase Process: Detail your research methods, user testing findings, and how you iterated based on feedback. Demonstrate your understanding of information architecture and user flows.

• Design System Expertise: Clearly present your experience with design systems, including their creation, maintenance, and impact on project efficiency.

• Technical Fluency: Be prepared to discuss your understanding of HTML/CSS and front-end frameworks and how it informs your design decisions.

Challenge Preparation:

• Workshop Simulation: Practice facilitating a hypothetical design discovery session. Focus on active listening, asking probing questions, and synthesizing information quickly.

• Case Study Analysis: Be ready to analyze a hypothetical business problem involving AI/data and propose a UX solution, outlining your design rationale and process.

• Technical Collaboration: Prepare to discuss how you'd collaborate with Data Scientists and ML Engineers, focusing on clear communication of design needs and understanding technical constraints.

📝 Enhancement Note: The emphasis on a portfolio review and potential case study/workshop simulation highlights the practical, hands-on nature of this role. Candidates should be prepared to articulate their design process and demonstrate their ability to work with complex, data-driven technologies.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: Essential for all aspects of UI/UX design, from wireframing and prototyping to high-fidelity mockups and design system component creation. Proficiency is a key requirement.

• Design Systems Tools: Experience with tools or methodologies for building and maintaining scalable design systems (often integrated within Figma or using dedicated platforms).

Analytics & Reporting:

• While not a primary focus for UX, familiarity with analytics tools (e.g., Google Analytics, or product analytics platforms) to understand user behavior and inform design decisions would be beneficial.

CRM & Automation:

Collaboration & Project Management:

• Slack: For day-to-day team communication and collaboration.

• Video Conferencing Tools: (e.g., Google Meet, Zoom) for client meetings, workshops, and team syncs.

• Project Management Tools: (e.g., Jira, Asana, Trello) potentially used for tracking design tasks and project progress.

📝 Enhancement Note: Figma is explicitly called out as a required tool. The company's focus on AI and data means that while direct experience with specific data analytics or ML platforms isn't required for the UX role, an understanding of their output and how users interact with data-heavy interfaces is crucial.

👥 Team Culture & Values

Operations Values:

• Innovation: A core value, driven by the company's position at the forefront of AI and data solutions. Expect a culture that encourages exploration of new ideas and technologies.

• Client Focus: As a premier partner, Datatonic prioritizes delivering exceptional value and solutions to its clients, meaning design work must be strategically aligned with client business objectives.

• Excellence & Expertise: A commitment to high-quality work, driven by deep technical expertise in AI, ML, and Google Cloud. Designers are expected to uphold high standards in their craft.

• Collaboration: Essential for bridging the gap between complex technical capabilities and user needs. Teamwork across disciplines (design, data science, engineering) is paramount.

• Continuous Learning: In the rapidly evolving fields of AI and cloud technology, a dedication to ongoing learning and skill development is highly valued.

Collaboration Style:

• Highly cross-functional, with designers working hand-in-hand with Data Scientists, ML Engineers, and Architects. This requires clear communication, empathy for different technical perspectives, and a shared goal of delivering impactful solutions.

• Agile and iterative, with frequent feedback loops from both internal teams and clients to ensure designs are aligned and effective.

• Open to experimentation and learning, encouraging designers to explore new approaches to AI interface design.

📝 Enhancement Note: The company culture is likely to be intellectually stimulating, fast-paced, and client-centric, characteristic of a successful tech consultancy. The emphasis on collaboration across technical disciplines is a key aspect for a UX designer in this environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for Ambiguity: AI and Generative AI are rapidly evolving fields, meaning user needs and optimal interface patterns may not always be clearly defined, requiring designers to navigate ambiguity and establish new standards.

• Bridging Technical Complexity and User Simplicity: Translating sophisticated AI/ML functionalities into intuitive, accessible user experiences for a broad range of users, from technical experts to business stakeholders.

• Client Expectations Management: Effectively communicating design rationale and managing expectations with clients who may have varying levels of technical understanding or specific business goals.

• Keeping Pace with AI Advancements: Continuously learning about new AI capabilities and trends to ensure designs remain relevant and leverage the latest technological possibilities.

Learning & Development Opportunities:

• AI/ML Specialization: Opportunities to become a specialist in designing user experiences for cutting-edge AI and Generative AI applications.

• Google Cloud Platform Expertise: Gaining deeper knowledge of GCP services and their implications for designing enterprise-level data solutions.

• Advanced UX Methodologies: Refining skills in areas like complex data visualization, predictive analytics interfaces, and human-AI interaction design.

• Consulting Skills: Developing stronger client-facing skills, workshop facilitation, and strategic advisory capabilities.

📝 Enhancement Note: The challenges presented are inherent to working at the cutting edge of AI and technology consulting. The growth opportunities are significant, offering a path to highly specialized and sought-after expertise in UX for AI.

💡 Interview Preparation

Strategy Questions:

• "How would you approach designing a user interface for a new Generative AI tool that assists businesses with content creation? What are the key considerations?" (Focus on user needs, AI capabilities, ethical considerations, and iterative design).

• "Describe a time you had to translate highly technical requirements from engineers or data scientists into a user-friendly design. How did you ensure alignment and feasibility?" (Highlight collaboration, communication, and problem-solving skills).

Company & Culture Questions:

• "What interests you specifically about Datatonic's work in AI and Google Cloud?" (Show genuine interest and research into the company's mission and client work).

• "How do you stay updated with the latest trends in UX design and AI?" (Demonstrate proactivity and a passion for learning).

Portfolio Presentation Strategy:

• Structure is Key: For each project, clearly define the problem, your specific role and contributions, the design process followed (research, ideation, prototyping, testing), key decisions made, challenges overcome, and the resulting impact or outcomes.

• Quantify Impact: Where possible, use metrics to demonstrate the success of your designs (e.g., improved user engagement, reduced task completion time, positive feedback).

• Showcase Process, Not Just Pixels: Emphasize your thought process, your research findings, and how user feedback informed your design iterations.

• Tailor to AI/Data: If possible, highlight projects that involved complex data, enterprise applications, or any form of AI/ML, even if indirect. If not, explain how your general UX principles apply to these domains.

• Be Ready for Questions: Anticipate questions about your design choices, alternative solutions, and how you handle constructive criticism.

📝 Enhancement Note: The interview preparation advice focuses on demonstrating strategic thinking, technical understanding, and a strong grasp of the UX design process, particularly within the context of AI and client-facing work.

📌 Application Steps

To apply for this UX Designer position:

• Submit your application through the provided link on Ashby.

• Tailor Your Resume: Customize your resume to highlight your 2-4 years of UX/UI design experience, emphasizing relevant skills such as Figma, design systems, user research, and any experience with complex web applications or data-intensive projects.

• Curate Your Portfolio: Carefully select 2-3 of your strongest projects that showcase your end-to-end design process, problem-solving abilities, and impact. Ensure it clearly demonstrates your capabilities in wireframing, prototyping, user research, and ideally, any exposure to AI or data-driven applications.

• Prepare Your Presentation: Practice presenting your portfolio projects concisely and effectively, focusing on the story behind each design: the problem, your process, your solutions, and the outcomes. Be ready to articulate your design rationale and defend your choices.

• Research Datatonic: Familiarize yourself with Datatonic's work, their partnership with Google Cloud, and their focus on AI/ML solutions. Understand their company culture and values to articulate your interest and fit.

⚠️ 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.