Senior Product Designer (AI experiences) (m/f/d)

📍 Job Overview

Job Title: Senior Product Designer (AI experiences) (m/f/d)

Company: Awin

Location: Iași, Romania; London, United Kingdom; Madrid, Spain; Milan, Italy; Warsaw, Poland

Job Type: Full-Time

Category: Product Design / UX/UI

Date Posted: April 20, 2026

Experience Level: 5-10 years

Remote Status: Hybrid

🚀 Role Summary

• Lead the design and development of AI-powered user experiences, with a specific focus on conversational interfaces and LLM integration.

• Drive product discovery for AI features, identifying high-impact use cases and translating complex AI capabilities into intuitive, trustworthy user interactions.

• Collaborate closely with Product Management, Engineering, and Data Science teams to understand AI model behavior, constraints, and user needs.

• Define and measure success metrics for AI experiences, ensuring they align with usability, trust, and business objectives.

• Contribute to the evolution of design principles, patterns, and governance for AI within the organization, while mentoring junior designers.

📝 Enhancement Note: This role is a pivotal position within Awin's product development, specifically focusing on the ethical and effective integration of AI. The emphasis on "responsible, human-centred AI experiences" and "trustworthy user experiences" indicates a need for a designer who can balance cutting-edge technology with user empathy and ethical considerations. The hybrid work model suggests a need for strong self-management and communication skills.

📈 Primary Responsibilities

• Spearhead the discovery phase for AI-driven features, including in-depth user research and market analysis to identify high-value use cases for Large Language Model (LLM) integration.

• Design end-to-end conversational flows, prompt engineering strategies, and nuanced interaction patterns for the company's AI chatbot.

• Translate intricate AI capabilities and probabilistic outputs into clear, understandable, and trustworthy user experiences across the platform.

• Develop interactive prototypes for AI interactions, meticulously accounting for edge cases, error states, and potential failure scenarios.

• Foster strong partnerships with Engineering and Data Science teams to gain a deep understanding of model behavior, technical constraints, and design trade-offs.

• Define, track, and analyze key performance indicators (KPIs) for AI experiences, focusing on usability, user trust, and overall effectiveness.

• Conduct rigorous user testing and evaluate AI outputs, iterating designs based on real-world feedback and performance data.

• Actively contribute to the establishment and refinement of organizational AI design principles, reusable patterns, and governance frameworks.

• Provide mentorship to other designers on AI design best practices and contribute to the expansion of the design system with new AI components.

📝 Enhancement Note: The responsibilities highlight a need for a designer who can navigate the complexities of AI, not just in terms of user interface but also in understanding the underlying technology and its implications. The emphasis on "prompt engineering strategies" and "probabilistic AI outputs" suggests a requirement for a designer comfortable with generative AI concepts and their user-facing manifestations.

🎓 Skills & Qualifications

Education: Bachelor's degree in Design, Human-Computer Interaction, Computer Science, or a related field, or equivalent practical experience.

Experience: 5-10 years of proven experience as a Senior Product Designer, with a strong track record of shipping digital products and a portfolio showcasing successful AI-driven or data-informed feature designs.

Required Skills:

• Demonstrated expertise in human-centered design principles and methodologies.

• Proven ability to translate complex business and user requirements into clear, actionable design solutions.

• Experience designing AI-powered features, ideally including LLM-based systems, generative AI, and conversational interfaces.

• Strong proficiency in interaction design, information architecture, visual communication, and content-led design strategies.

• Ability to design for ambiguity, edge cases, and probabilistic AI outputs while maintaining clarity and user trust.

• Experience collaborating effectively with cross-functional teams, including Engineering, Product Management, and Data Science, understanding technical constraints and trade-offs.

• Confidence in prototyping and user testing AI interactions, including prompt design, flow design, and failure state handling.

Preferred Skills:

• Experience with prompt engineering or working closely with prompt engineers.

• Familiarity with AI ethics, responsible AI design principles, and AI governance frameworks.

• Experience contributing to or managing design systems, especially those incorporating AI components.

• Knowledge of affiliate marketing platforms or e-commerce ecosystems.

• Mentorship experience for junior design team members.

📝 Enhancement Note: The "About you" section is crucial here. It explicitly calls for experience with "AI-powered or data-driven features, ideally including LLM-based systems and conversational interfaces." This is a key differentiator for this role. The requirement for designing for "ambiguity, edge cases, and probabilistic AI outputs" is also a critical indicator of the specialized skills needed.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase a minimum of 2-3 significant projects demonstrating end-to-end product design ownership, with a strong emphasis on AI-driven or data-informed features.

• Clearly articulate the problem statement, your design process, the challenges encountered, and the solutions implemented, particularly for AI interactions.

• Provide detailed case studies of conversational interface design, including examples of flow mapping, prompt design, and user testing for AI outputs.

• Include examples of how you translated complex AI capabilities into intuitive and trustworthy user experiences, with demonstrable user impact.

Process Documentation:

• Demonstrate a structured approach to user research and discovery for AI features, including methodologies for identifying high-value AI use cases.

• Detail your process for designing and prototyping conversational flows, prompt interactions, and handling edge cases and failure states in AI systems.

• Explain your collaboration process with Engineering and Data Science teams, highlighting how you manage technical constraints and iterate on AI model behavior.

• Showcase your approach to defining and measuring success metrics for AI experiences, including usability testing and evaluation of AI outputs.

📝 Enhancement Note: For a Senior Product Designer role, especially one focused on AI, the portfolio is paramount. The emphasis should be on demonstrating the ability to handle the unique challenges of AI design, such as ambiguity and probabilistic outcomes, and how the candidate has successfully navigated these. The "Process Documentation" section further reinforces the need to articulate a systematic approach to AI product development.

💵 Compensation & Benefits

Salary Range: Based on typical Senior Product Designer roles with AI specialization in London, Madrid, Milan, and Warsaw, and considering the hybrid work model, a competitive salary range can be estimated.

• London, UK: £70,000 - £95,000 per annum.

• Madrid, Spain: €55,000 - €75,000 per annum.

• Milan, Italy: €55,000 - €75,000 per annum.

• Warsaw, Poland: 180,000 - 250,000 PLN per annum.

• Iași, Romania: 130,000 - 180,000 RON per annum.

These estimates are based on industry benchmarks for senior-level design roles, factoring in the specialized AI experience, company size (Awin is a well-established global company), and cost of living in these major European cities. The actual salary will depend on the candidate's specific experience, qualifications, and the final location within the specified countries.

Benefits:

• Comprehensive health insurance and wellness programs.

• Generous paid time off (holiday, sick leave, parental leave).

• Opportunities for professional development, including training, conferences, and access to learning resources.

• Hybrid work model offering flexibility and work-life balance.

• Participation in global social activities and team-building events.

• Inclusive and diverse company culture that champions uniqueness and authenticity.

• Potential for stock options or performance-based bonuses (common in tech companies).

• Pension scheme contributions.

Working Hours: 40 hours per week, with flexibility offered within the hybrid work arrangement, allowing for a balanced approach to project delivery and personal commitments.

📝 Enhancement Note: Given the multiple international locations and the absence of a specific salary range in the input, a region-appropriate estimate has been provided. This includes ranges for each major city listed, reflecting local market conditions and cost of living. The benefits have been inferred from standard offerings at a company of Awin's size and industry, with specific mention of "Inclusive culture," "Social activities," and "Professional development" as highlighted in the job description.

🎯 Team & Company Context

🏢 Company Culture

Industry: Affiliate Marketing & Partnership Ecosystem. Awin operates as a leading global affiliate marketing network, connecting advertisers with publishers to drive performance-based marketing campaigns. The company is part of the Axel Springer group, a major European media and technology company. This context means the operations involve complex data management, partner relations, and platform development to facilitate digital advertising and e-commerce.

Company Size: Awin is a significant player in its industry, likely falling into the "Large Enterprise" category (over 1,000 employees), given its global presence and its parent company's scale. This size implies established processes, a global reach, and access to substantial resources, while also requiring efficient internal operations to manage diverse teams and markets.

Founded: Established in 2000, Awin has a long-standing history in the digital marketing space, indicating stability and a deep understanding of the evolving affiliate landscape. This longevity suggests a company that can adapt to market changes and invest in innovation, such as AI-driven experiences.

Team Structure: The Senior Product Designer will be part of a product development team that includes Product Managers, Engineers (likely full-stack, front-end, and back-end), Data Scientists, and potentially other Designers (UX researchers, UI designers). The design team itself likely has a lead or manager, and the Senior Designer will be expected to mentor junior members. Collaboration will be cross-functional, with strong ties to Product and Engineering for feature development and AI model integration.

Methodology: Awin likely employs agile development methodologies (e.g., Scrum, Kanban) for product development. For AI initiatives, this would involve iterative design and development cycles, close collaboration with data teams for model training and evaluation, and a focus on continuous improvement based on user feedback and performance metrics. The company emphasizes "human-centred design" and "responsible AI," suggesting a methodology that prioritizes ethical considerations and user needs alongside technical feasibility.

Company Website: https://www.awin.com/

📝 Enhancement Note: The company's industry (Affiliate Marketing) and its parent company (Axel Springer) provide crucial context for the operations role. The AI focus within this structure suggests the company is leveraging technology to enhance its core business of connecting advertisers and publishers, likely through better tools, insights, and user experiences for its partners.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a Senior Product Designer, indicating a mid-to-senior level of expertise. It requires a designer who can operate with a high degree of autonomy, lead design initiatives for complex features, and mentor others. The focus on AI experiences suggests a specialization that is in high demand and offers significant growth potential within the tech and product design fields.

Reporting Structure: The Senior Product Designer will likely report to a Head of Product Design, Design Manager, or a Senior Product Lead. They will work closely with Product Managers for feature roadmapping and requirements, and with Engineering leads for implementation feasibility. Collaboration will extend to Data Science teams responsible for AI model development and performance.

Operations Impact: The Senior Product Designer's work will directly impact Awin's platform by shaping how users interact with advanced AI capabilities. This includes improving user engagement with AI chatbots, enhancing the utility of AI-driven insights for advertisers and publishers, and ensuring the trustworthiness of AI outputs. Successful AI experiences can lead to increased user adoption, higher conversion rates for affiliate campaigns, and a stronger competitive position for Awin in the market. The role also influences the broader design strategy and AI ethics within the company.

Growth Opportunities:

• Specialization Advancement: Deepen expertise in AI product design, conversational AI, and prompt engineering, becoming a go-to expert within Awin and potentially the broader industry.

• Leadership Development: Transition into a Design Lead or Manager role, taking on more strategic responsibilities, managing a team, and influencing product roadmaps.

• Cross-Functional Mobility: Move into Product Management roles, leveraging design expertise to define product strategy, or into specialized AI ethics or UX research roles.

• Broader Impact: Contribute to shaping Awin's overall AI strategy and product vision, influencing how AI is integrated across the entire ecosystem.

• Continuous Learning: Access to industry conferences, workshops, and internal training focused on the latest advancements in AI, design, and user experience.

📝 Enhancement Note: The "Senior" title, combined with the AI specialization, points to a role with significant responsibility and potential for career advancement. The growth opportunities are framed around deepening AI expertise, moving into leadership, or leveraging design skills in related product functions.

🌐 Work Environment

Office Type: Awin operates a hybrid work model. This means employees will have the flexibility to work from home and from a physical Awin office location. The office spaces are likely designed to foster collaboration, innovation, and a sense of community, equipped with the necessary technology for both individual work and team meetings.

Office Location(s): The role is open to candidates in Iași (Romania), London (UK), Madrid (Spain), Milan (Italy), and Warsaw (Poland). This distributed model allows Awin to tap into a global talent pool and offers employees flexibility in choosing their primary work location within these regions. Specific office addresses would need to be confirmed, but these are major cities with established business hubs.

Workspace Context:

• Collaborative Environment: The hybrid model necessitates a culture that supports seamless collaboration between remote and in-office team members. Expect regular virtual and in-person meetings, workshops, and brainstorming sessions.

• Tools & Technology: Access to industry-standard design and collaboration tools (e.g., Figma, Sketch, Adobe Creative Suite, Slack, Jira, Confluence) will be provided. Specific AI development and testing tools will also be available.

• Team Interaction: Opportunities for informal "water cooler" chats and formal team syncs, both virtually and in office, to build relationships and foster a sense of belonging. The company's emphasis on "Life @ Awin" hub for virtual social activities underscores this commitment.

Work Schedule: The standard work schedule is 40 hours per week. The hybrid nature of the role offers flexibility in terms of when and where work is performed, within reasonable bounds to ensure team synchronicity and project progress. This flexibility is particularly beneficial for designers who may need dedicated focus time for deep work.

📝 Enhancement Note: The hybrid model is a key aspect of the work environment, implying a need for strong remote collaboration skills. The mention of "Life @ Awin" hub for virtual social activities suggests a proactive approach to maintaining company culture across distributed teams.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review your application and portfolio to assess basic qualifications and alignment with the role.

• Hiring Manager Interview: A conversation with the hiring manager to discuss your experience, motivations, and high-level fit for the team and role.

• Portfolio Presentation & Design Challenge: You will likely be asked to present a detailed case study from your portfolio, focusing on an AI-related project or a complex design problem. This may be followed by a take-home design challenge or an in-person/virtual whiteboard exercise to assess your problem-solving skills, design process, and ability to think on your feet, especially concerning AI interactions.

• Cross-Functional Interviews: Interviews with key stakeholders, such as Product Managers, Engineers, and Data Scientists, to evaluate your collaboration style, technical understanding, and ability to work effectively within a cross-functional team.

• Final Interview: A concluding interview, potentially with a senior leader, to assess cultural fit, leadership potential, and overall alignment with Awin's vision.

Portfolio Review Tips:

• Highlight AI Experience: Prioritize showcasing projects that demonstrate your experience with AI, LLMs, or data-driven features. Clearly explain the AI components and your role in designing them.

• Structure for Clarity: Organize your portfolio with a clear narrative for each project: problem, your approach, key decisions, challenges, solutions, and outcomes (with metrics).

• Showcase Process: Detail your design process, especially how you handled ambiguity, user research for novel AI interactions, and collaboration with technical teams.

• Focus on Impact: Quantify the impact of your designs whenever possible, using data and metrics to demonstrate user value and business success.

• Prepare for AI-Specific Questions: Be ready to discuss AI ethics, responsible AI design, prompt engineering considerations, and how you design for probabilistic outcomes.

Challenge Preparation:

• Understand the Problem: If given a design challenge, carefully analyze the prompt, ask clarifying questions, and define your scope.

• Think Aloud: For live challenges, articulate your thought process clearly, explaining your assumptions and rationale.

• Focus on AI Nuances: Consider how AI specifically impacts the problem – e.g., data requirements, potential biases, user trust, and iterative learning.

• Present Solutions Holistically: Whether it's a case study presentation or a challenge, present a well-rounded solution that considers user experience, technical feasibility, and business goals.

📝 Enhancement Note: The interview process for a senior AI-focused role will likely involve a more rigorous assessment of technical understanding and problem-solving capabilities related to AI. The portfolio presentation is a critical component, and candidates should be prepared to deep-dive into their AI design work.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping: Figma, Sketch, Adobe Creative Suite (Photoshop, Illustrator, XD), InVision, Axure RP.

• Collaboration & Project Management: Jira, Confluence, Asana, Trello, Slack, Microsoft Teams.

• User Research & Testing: UserTesting.com, Maze, Lookback, Hotjar, SurveyMonkey, Typeform.

Analytics & Reporting:

• Web Analytics: Google Analytics, Adobe Analytics.

• Data Visualization: Tableau, Power BI, Looker (or similar BI tools for understanding AI performance data).

• Product Analytics: Amplitude, Mixpanel, Pendo.

CRM & Automation:

• CRM: Salesforce, HubSpot (Awin's internal CRM for managing advertiser/publisher relationships).

• Automation Tools: Potentially internal tools or platforms for managing affiliate campaigns and data flows.

• AI/ML Platforms: Familiarity with concepts or platforms used in AI development (e.g., cloud AI services like AWS SageMaker, Google AI Platform, Azure ML) would be beneficial, though direct development is not expected.

📝 Enhancement Note: While the job description doesn't explicitly list the tech stack, these are industry-standard tools for product designers, particularly in a hybrid, global tech company. The inclusion of AI/ML platforms is inferred from the role's focus.

👥 Team Culture & Values

Operations Values:

• Human-Centred Design: A core value emphasizing the user at the heart of all design decisions, ensuring AI solutions are beneficial and intuitive for customers.

• Transparency & Trust: Particularly crucial for AI, Awin likely values designs that are clear about AI capabilities, limitations, and data usage, fostering user trust.

• Collaboration & Inclusivity: As highlighted, Awin champions a dynamic, social, and inclusive culture, valuing diverse perspectives and encouraging teamwork across global teams.

• Innovation & Adaptability: A commitment to staying at the forefront of technology, especially AI, and adapting to market changes to provide leading solutions.

• Data-Driven Decisions: Utilizing data and user feedback to inform design choices and measure the effectiveness of AI experiences.

Collaboration Style:

• Cross-Functional Integration: Strong emphasis on working closely with Product, Engineering, and Data Science teams, fostering open communication and shared ownership of product outcomes.

• Agile & Iterative: A collaborative approach that embraces agile methodologies, allowing for frequent feedback loops, rapid iteration, and continuous improvement of AI features.

• Knowledge Sharing: A culture that encourages sharing best practices, design patterns, and insights, particularly around AI design, to elevate the entire team's capabilities.

• Feedback-Rich Environment: Open to constructive feedback from peers, stakeholders, and users, using it as a tool for growth and refinement of AI experiences.

📝 Enhancement Note: The company's explicit mention of "dynamic, social and inclusive culture" and "Diversity & Inclusion are paramount" directly informs the team culture and values section. The focus on AI also implies values related to responsibility, transparency, and ethical considerations.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for AI Ambiguity: Navigating the inherent unpredictability of LLM outputs and designing user experiences that are robust, clear, and manage user expectations effectively.

• Building Trust in AI: Overcoming potential user skepticism or fear of AI by designing transparent, reliable, and beneficial AI interactions.

• Cross-Team Alignment: Ensuring consistent understanding and collaboration between design, product, engineering, and data science teams, especially when dealing with complex AI models and their constraints.

• Ethical AI Implementation: Adhering to and contributing to responsible AI design principles, ensuring fairness, avoiding bias, and maintaining user privacy in AI-driven features.

• Rapidly Evolving Field: Keeping pace with the fast-moving advancements in AI technology and design best practices to ensure Awin's AI experiences remain cutting-edge.

Learning & Development Opportunities:

• AI Design Specialization: Deepen expertise in designing for LLMs, prompt engineering, conversational AI, and generative AI through internal projects, external training, and industry conferences.

• Leadership & Mentorship: Opportunities to mentor junior designers, lead design initiatives, and develop strategic product thinking skills for career progression into lead or management roles.

• Industry Exposure: Access to Awin's participation in industry events and partnerships, providing insights into the broader affiliate marketing and AI technology landscape.

• Cross-Disciplinary Learning: Gain a deeper understanding of AI model development, data science principles, and product strategy through close collaboration with respective teams.

📝 Enhancement Note: The challenges section directly addresses the unique complexities of designing AI experiences, which are critical for a candidate to understand and prepare for. The growth opportunities are tailored to leveraging these challenges into career development.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed an AI-powered feature. What was the problem, your approach, and the outcome?" (Focus on your process for handling AI ambiguity, user trust, and collaboration.)

• "How would you approach designing a conversational AI experience for [specific Awin use case, e.g., helping advertisers find publishers]? What are the key considerations for prompt design and flow?" (Demonstrate your understanding of conversational design principles and LLM capabilities.)

• "Imagine an AI chatbot provides an incorrect or unhelpful response. How would you design the user experience to handle this gracefully and maintain user trust?" (Assess your ability to design for edge cases and failure states.)

Company & Culture Questions:

• "What excites you about Awin and our mission in the affiliate marketing space?" (Research Awin's business model, market position, and recent news.)

• "How do you see AI impacting the future of affiliate marketing?" (Showcase your forward-thinking perspective and industry awareness.)

• "Awin values inclusivity and diversity. How do you contribute to an inclusive team environment and design for diverse user groups?" (Reflect on your experience and commitment to these values.)

Portfolio Presentation Strategy:

• AI Case Study Deep Dive: Select a project that best demonstrates your AI design skills. Be prepared to walk through the entire process, from research to implementation and impact.

• Focus on Design Decisions: Clearly articulate why you made specific design choices, especially those related to AI functionality, user interaction, and data handling.

• Quantify Impact: Use data and metrics to showcase the success of your designs. If direct metrics are unavailable, articulate the anticipated impact and how you would measure it.

• Discuss Learnings: Be open about challenges faced and lessons learned. This demonstrates self-awareness and a growth mindset, which is crucial for senior roles.

• Interactive Elements: If possible, prepare a live demo or interactive prototype to showcase key AI interactions.

📝 Enhancement Note: The interview preparation section is tailored to the specific AI focus of the role, incorporating common questions for senior designers and AI-specific challenges. The portfolio presentation strategy emphasizes showcasing AI design expertise and understanding.

📌 Application Steps

To apply for this Senior Product Designer (AI experiences) position:

• Submit your application through the provided link on Greenhouse.

• Tailor your Resume: Ensure your resume highlights your experience with AI, LLM integration, conversational interfaces, and human-centered design. Use keywords from the job description.

• Curate your Portfolio: Select 2-3 of your strongest projects that best showcase your AI design capabilities, process, and impact. Prepare detailed case studies for each.

• Prepare your AI Design Narrative: Be ready to discuss your approach to designing for AI ambiguity, building user trust, and collaborating with technical teams. Practice presenting your portfolio, focusing on your AI-related projects.

• Research Awin: Understand Awin's business, its role in affiliate marketing, and its parent company, Axel Springer. Familiarize yourself with their current AI initiatives or related technologies if possible.

• Practice Behavioral Questions: Prepare for questions about your experience, collaboration style, and how you handle challenges, especially those related to complex technology and cross-functional teamwork.

⚠️ 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.