AI Product Designer

📍 Job Overview

Job Title: AI Product Designer

Company: dentsu

Location: Bengaluru, India

Job Type: Full-time

Category: Product Design / User Experience (UX) / AI Product Development

Date Posted: March 31, 2026

Experience Level: 5+ years

🚀 Role Summary

• Lead the end-to-end user experience design for Dentsu's advanced AI-powered agentic tools and client-facing data products, focusing on simplifying complex systems for non-technical users.

• Design intuitive and engaging interfaces for multi-agent systems, conversational data exploration, and automated reporting dashboards, ensuring seamless integration of AI capabilities into user workflows.

• Develop and maintain a robust design system for the Decisioning practice's AI product suite, ensuring consistency and scalability across all AI-driven user experiences.

• Conduct in-depth user research with internal media teams and external clients to identify pain points, map user journeys, and validate design decisions for AI product enhancements.

• Collaborate closely with AI engineers and data scientists to translate complex AI functionalities into user-friendly designs, ensuring technical feasibility and high-fidelity execution.

📝 Enhancement Note: This role is positioned as a senior product design position within dentsu's AI product development efforts, specifically focusing on making sophisticated AI tools accessible and valuable to media professionals and clients. The emphasis is on bridging the gap between cutting-edge AI technology and practical, user-centric design.

📈 Primary Responsibilities

• Spearhead the complete product design lifecycle for agentic AI tools, from initial discovery and user research to detailed wireframing, interactive prototyping, and defining production-ready design specifications.

• Craft user-friendly interfaces for sophisticated multi-agent systems designed to assist media planners, analysts, and clients with diverse technical backgrounds.

• Architect intuitive user experience (UX) flows for "Genie spaces," enabling conversational data exploration and the creation of automated reporting dashboards that deliver actionable insights without requiring direct coding or complex query languages.

• Establish and evolve a comprehensive design system for the Decisioning practice's AI product portfolio, ensuring consistent visual language, interaction patterns, and component reusability across all AI tools.

• Execute comprehensive user research initiatives within enterprise B2B contexts, employing methods such as stakeholder interviews, contextual inquiry, and usability testing to deeply understand user needs and validate design concepts.

• Design clear patterns for transparency and trust in AI-driven experiences, focusing on how users can understand the system's actions, reasoning, and mechanisms for correction.

• Develop and test innovative interaction models for critical AI system functionalities, including human-agent handoffs, robust error recovery processes, and multi-step automated workflow management.

• Foster strong, collaborative relationships with AI engineers and data scientists, ensuring design solutions are technically viable and implemented with high fidelity and attention to detail.

• Create effective onboarding flows and accompanying training materials designed to accelerate user adoption and proficiency with new AI tools across various agency teams.

• Produce client-facing presentation materials, compelling product demonstrations, and polished visual assets that clearly articulate the capabilities and tangible business value of the AI tools.

📝 Enhancement Note: The responsibilities highlight a full-spectrum product design role, requiring not only creative design skills but also strategic thinking, strong collaboration with technical teams, and a deep understanding of enterprise user needs. The focus on "Genie spaces" and conversational data exploration suggests a forward-thinking approach to data interaction within the media industry.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Design, Human-Computer Interaction (HCI), Computer Science, or a related field is typically expected for senior product design roles.

Experience: 5+ years of dedicated product design experience with a proven track record of shipping successful B2B or data-intensive products. Demonstrated expertise in designing complex workflows, effective data visualization, and scaling enterprise UX solutions.

Required Skills:

• Product Design Leadership: Ability to lead end-to-end design processes for AI-powered products from concept to launch.

• User Experience (UX) Design: Deep understanding of UX principles, user-centered design methodologies, and creating intuitive digital experiences.

• Complex Workflow Design: Proven experience in mapping, designing, and optimizing intricate multi-step user workflows.

• Data Visualization: Expertise in designing clear, insightful, and actionable data visualizations for diverse user needs.

• Enterprise UX: Experience in designing scalable and robust user experiences for large organizations and complex systems.

• Figma Proficiency: Advanced skills in Figma, including mastery of component libraries, auto-layout features, and creating sophisticated interactive prototypes.

• AI/ML Product Design: Experience designing user interfaces and interactions for products powered by Artificial Intelligence and Machine Learning.

• Conversational Interfaces: Familiarity and experience in designing user interactions for chatbots, voice interfaces, or other conversational AI applications.

• Design Systems: Strong understanding of design system principles and experience working with or building component-based design methodologies.

• User Research: Proficiency in various user research methodologies, including stakeholder interviews, usability testing, and journey mapping, specifically within B2B enterprise contexts.

• Visual Design: Excellent visual design capabilities with a keen eye for typography, layout, color theory, and overall information hierarchy.

• Communication & Collaboration: Superior verbal and written communication skills, with the ability to articulate design rationale effectively to cross-functional teams (engineering, product, business) and present design solutions compellingly.

• Distributed Team Collaboration: Proven ability to work effectively and collaboratively with teams spread across different geographic locations and time zones.

Preferred Skills:

• Media/Advertising Tech: Prior experience within the media, advertising, or marketing technology industries.

• Data/Analytics Platforms: Familiarity with platforms such as Databricks, Power BI, Tableau, or similar data and analytics tools from a design perspective.

• Agent-Based Interaction Design: Specific experience designing chatbot, copilot, or agent-based interaction patterns.

• Business Intelligence (BI) Design: Background in designing products for business intelligence, analytics, or dashboarding applications.

• Motion Design/Micro-interactions: Experience incorporating motion design or micro-interactions to enhance user experience, particularly for complex state transitions in AI workflows.

• Accessibility (WCAG): Knowledge of and experience applying accessibility standards (WCAG) to enterprise applications.

• Design System Development: Experience contributing to or building design systems from the ground up.

📝 Enhancement Note: The qualifications emphasize a blend of advanced design execution skills (Figma, visual design), strategic thinking (workflow design, enterprise UX), and specialized knowledge in AI and data-driven products. The preference for industry experience and familiarity with specific data platforms suggests a desire for candidates who can hit the ground running within Dentsu's operational context.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Shipped B2B or Data-Heavy Products: Showcase at least 2-3 significant projects demonstrating end-to-end design ownership for products used in a business context or heavily reliant on data.

• Complex Workflow Solutions: Include case studies that detail the process of understanding, mapping, and designing solutions for complex, multi-step workflows, highlighting efficiency gains or user pain point resolution.

• Data Visualization Case Studies: Present examples of how you've translated complex data into clear, actionable, and aesthetically pleasing visualizations that drive user understanding and decision-making.

• AI/ML Product Design Examples: Feature projects where you've designed user interfaces or interactions for AI/ML-powered features or products, illustrating how you made these complex technologies accessible.

• Design System Contributions: If applicable, include examples of your involvement with design systems, showcasing component design, pattern library contributions, or system governance.

• Prototyping & Interaction Design: Demonstrate interactive prototypes (ideally from Figma) that clearly illustrate key user flows, interaction models, and the overall user experience of your designed products.

Process Documentation:

• User Research Synthesis: For each relevant project, provide clear documentation of the user research conducted, including methodologies used, key findings, and how these insights directly informed design decisions.

• Design Process Walkthrough: Clearly articulate your design process for selected projects, detailing stages from problem definition, ideation, wireframing, prototyping, testing, to handoff, emphasizing iterative improvements.

• Collaboration & Handoff: Illustrate your collaboration process with engineering and product management, including how you documented specifications, managed feedback, and ensured successful implementation of your designs.

• Problem-Solving & Iteration: Showcase instances where your designs faced challenges or required significant iteration, detailing the problem, your approach to solving it, and the resulting improvements.

📝 Enhancement Note: The portfolio requirements are geared towards demonstrating practical application of advanced design skills in complex, enterprise-level scenarios, with a specific emphasis on AI and data. Candidates should be prepared to articulate their design process, research findings, and the impact of their work with quantifiable results where possible.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Senior Product Designers with 5+ years of experience in major tech hubs in India, particularly Bengaluru, and considering the specialized nature of AI product design, the estimated annual salary range would be ₹15,00,000 to ₹28,00,000. This range can vary based on the candidate's specific experience, skill set, and the final negotiation.

Benefits:

• Health & Wellness: Comprehensive health insurance (medical, dental, vision) for employees and dependents.

• Retirement Savings: Provident Fund (PF) contributions and other retirement planning support as per Indian regulations.

• Paid Time Off: Generous annual leave, sick leave, and public holidays.

• Professional Development: Opportunities for continuous learning, including access to training programs, workshops, conferences, and online courses related to AI, UX, and product design.

• Performance Bonuses: Potential for performance-based bonuses tied to individual and company achievements.

• Employee Assistance Program (EAP): Confidential support services for personal and professional challenges.

• Flexible Work Arrangements: While this role is listed as on-site, Dentsu may offer some flexibility for specific needs or hybrid arrangements depending on team and company policy.

• Commuting Support: Potential for transportation allowances or facilities, common for large corporate offices in Bengaluru.

Working Hours:

Standard full-time working hours are typically 40 hours per week. The role is based in India (Asia/Kolkata time zone). While the role is on-site, core working hours will likely align with standard business operations, with potential for flexibility depending on project needs and team collaboration requirements, especially when working with globally distributed teams.

📝 Enhancement Note: The salary estimate is derived from research of similar Senior Product Designer roles in Bengaluru, India, factoring in the specialized AI and enterprise UX requirements. Benefits are typical for large multinational corporations operating in India. The working hours are standard, but the need for global collaboration might necessitate occasional adjustments.

🎯 Team & Company Context

🏢 Company Culture

Industry: Dentsu is a global leader in advertising and marketing communications, operating across a wide spectrum of services including advertising, digital transformation, customer experience, and technology. They are at the forefront of integrating AI and data into marketing and client solutions.

Company Size: Dentsu Aegis Network (DAN) is a significant part of Dentsu, employing tens of thousands of people globally. This indicates a large, established organization with extensive resources, structured processes, and opportunities for career advancement.

Founded: Dentsu was founded in 1906 in Japan. Dentsu Aegis Network was formed in 2014 through the integration of Dentsu's international businesses. This long history signifies stability, deep industry expertise, and a culture that has evolved over decades.

Team Structure:

• The AI Product Designer will likely be part of a dedicated AI product development team or a specialized "Decisioning practice" within Merkle (a Dentsu company).

• This team will comprise AI engineers, data scientists, product managers, and potentially other designers.

• The structure is expected to be collaborative and cross-functional, fostering close interaction between design, engineering, and product strategy.

Methodology:

• Data-Driven Decision Making: Dentsu heavily relies on data analytics to inform strategy and product development. The AI product team will leverage data insights to guide design and feature prioritization.

• Agile Development: It's highly probable that the team operates under an Agile framework (e.g., Scrum or Kanban) to facilitate iterative development, rapid prototyping, and continuous feedback loops.

• User-Centric Design: A core methodology will be user-centered design, ensuring that all product development, especially AI features, is grounded in a deep understanding of user needs and pain points.

• Design Thinking: The application of design thinking principles is likely prevalent, focusing on empathy, ideation, prototyping, and testing to solve complex problems.

Company Website: https://www.dentsu.com/global/en/

📝 Enhancement Note: Joining Dentsu means becoming part of a global advertising and technology powerhouse with a rich history. The AI product team operates within a large, structured environment that values data-driven insights, user-centricity, and agile methodologies. The role offers exposure to cutting-edge AI applications within the marketing and media landscape.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as a Senior Product Designer. It signifies a level of expertise where individuals are expected to lead significant design initiatives, mentor junior team members, and have a substantial impact on product strategy and execution. The "AI Product Designer" title indicates a specialization within product design, focusing on a high-demand and evolving field.

Reporting Structure: The Senior AI Product Designer will likely report to a Design Manager, Head of Product Design, or a Product Lead overseeing the AI product suite. They will collaborate closely with Product Managers, AI Engineers, Data Scientists, and potentially other designers and researchers within Merkle or Dentsu's technology divisions.

Operations Impact: The Senior AI Product Designer will have a direct and significant impact on Dentsu's ability to leverage AI for its clients and internal operations. Their work will:

• Enhance Client Value: By creating intuitive AI tools, they will enable clients to derive deeper insights from data, optimize campaigns more effectively, and achieve better business outcomes.

• Improve Internal Efficiency: Designing user-friendly agentic tools can streamline workflows for media planners and analysts, reducing manual effort and increasing productivity.

• Drive Product Innovation: Their design leadership will be critical in shaping the future direction of Dentsu's AI product portfolio, ensuring it remains competitive and innovative.

• Influence Technology Adoption: By making complex AI systems usable, they will accelerate the adoption of these technologies across Dentsu's agencies and client base.

Growth Opportunities:

• Specialization in AI/ML Design: Deepen expertise in designing for cutting-edge AI technologies, becoming a recognized leader in this niche field.

• Leadership Roles: Progress into Lead Product Designer, Design Manager, or Head of Product Design positions, managing teams and setting design strategy for larger product portfolios.

• Cross-Functional Mobility: Transition into Product Management, UX Research Leadership, or even AI Strategy roles, leveraging a strong understanding of both design and technology.

• Global Exposure: Work on projects with global impact, collaborating with teams and stakeholders across Dentsu's international network.

• Industry Recognition: Contribute to industry best practices and potentially speak at conferences on AI product design and user experience.

📝 Enhancement Note: This senior role offers substantial growth potential, both in terms of specialized AI design expertise and broader leadership responsibilities within a global organization. The impact of the role is significant, directly contributing to Dentsu's strategic goals in AI and data-driven solutions.

🌐 Work Environment

Office Type: The role is based at the DGS India - Bengaluru - Manyata N1 Block office, indicating a large, modern corporate campus or office building typical of major technology and advertising firms in India. This environment is likely designed to foster collaboration and productivity.

Office Location(s): The primary specified location is Bengaluru, Karnataka, India. Dentsu operates globally, with offices in numerous major cities worldwide, but this specific role is tied to the Bengaluru operations.

Workspace Context:

• Collaborative Spaces: The office environment will likely feature a mix of open-plan workspaces, dedicated team areas, meeting rooms, and potentially quiet zones for focused work. This setup encourages interaction and knowledge sharing among team members.

• Technology & Tools: Expect access to modern hardware, high-speed internet, and the necessary software licenses for design tools (Figma), collaboration platforms (Slack, Teams), and potentially internal Dentsu systems.

• Team Interaction: The on-site nature of the role facilitates direct, in-person collaboration with local team members, including AI engineers, data scientists, and product managers. This proximity can lead to more efficient problem-solving and stronger team cohesion.

• Amenities: Large corporate offices often provide amenities such as cafeterias, recreational areas, and potentially wellness facilities, contributing to a positive employee experience.

Work Schedule: The role is full-time and on-site, with standard working hours likely aligning with Indian business hours (Asia/Kolkata time zone). However, due to Dentsu's global presence, there may be a need to coordinate with teams in different time zones, which could occasionally involve early morning or late evening calls.

📝 Enhancement Note: The on-site work environment in a major corporate hub like Bengaluru suggests a professional, collaborative, and well-equipped setting. The emphasis on in-person collaboration is a key aspect of the work environment for this role.

📄 Application & Portfolio Review Process

Interview Process:

1. Application Screening: Initial review of resumes and portfolios to assess alignment with required qualifications and experience.

2. Hiring Manager/Recruiter Screen: A preliminary call to discuss the role, the candidate's background, career aspirations, and initial fit. This stage often includes a high-level overview of the candidate's portfolio.

3. Design Challenge/Portfolio Review: A more in-depth session where the candidate presents their portfolio, walking through 1-3 key projects. This is often followed by a design exercise or discussion on hypothetical design problems relevant to AI product design.

4. Team Interviews: Interviews with cross-functional team members (e.g., Product Manager, AI Engineer, Data Scientist) to assess collaboration skills, technical understanding, and problem-solving approach.

5. Final Interview: A discussion with senior leadership (e.g., Head of Product Design, Director of Technology) to evaluate strategic thinking, cultural fit, and overall leadership potential.

Portfolio Review Tips:

• Curate Strategically: Select 3-4 projects that best showcase your experience with AI/ML products, complex workflows, data visualization, and enterprise UX. Prioritize projects that demonstrate end-to-end ownership.

• Tell a Story: For each project, structure your presentation around the problem statement, your role and process, the challenges faced, the solutions you designed, and the impact/outcomes achieved. Use visuals effectively.

• Highlight AI/Data Nuances: Clearly explain how you approached the unique challenges of designing for AI (e.g., transparency, trust, human-AI interaction) and data-heavy interfaces.

• Showcase Figma Skills: Be prepared to demonstrate your proficiency in Figma, especially regarding components, auto-layout, and interactive prototyping, perhaps by sharing specific screens or flows.

• Quantify Impact: Wherever possible, include metrics or qualitative feedback that demonstrate the success of your designs (e.g., improved user efficiency, increased data comprehension, positive user feedback).

• Be Ready for Questions: Anticipate questions about your design decisions, trade-offs you made, how you handled disagreements, and how you would approach future challenges.

Challenge Preparation:

• Understand the Domain: Familiarize yourself with Dentsu's business, the advertising/media technology industry, and common challenges in AI product development within this space.

• Practice Design Exercises: Be prepared for hypothetical design problems. Practice breaking down problems, brainstorming solutions, sketching wireframes, and articulating your thought process. Focus on your approach to user needs and AI constraints.

• Prepare for Technical Discussions: While not an engineering role, understand the basics of AI/ML and data systems to discuss feasibility and collaboration with engineers. Be ready to talk about user research and validation methods.

• Articulate Design Rationale: Practice clearly explaining why you made certain design decisions, focusing on user needs, business goals, and technical considerations.

📝 Enhancement Note: The interview process is designed to thoroughly assess a candidate's design skills, strategic thinking, technical understanding, and cultural fit. A strong, well-articulated portfolio is crucial, and candidates should prepare for both presentation and problem-solving exercises tailored to the AI product design domain.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: The core tool for wireframing, prototyping, UI design, and collaboration. Mastery of its advanced features (components, auto-layout, interactive prototyping) is essential.

• Design System Tools: Proficiency with tools used to manage and distribute design systems (e.g., Figma's library features, potentially specialized tools like Zeroheight).

Analytics & Reporting (Familiarity):

• Data Visualization Tools (e.g., Tableau, Power BI, Looker): While not a primary design tool, familiarity with how data is visualized and presented in these platforms will inform the design of dashboards and reporting features.

• Analytics Platforms (e.g., Google Analytics, Adobe Analytics): Understanding how user behavior data is tracked and analyzed is beneficial for designing data-informed products.

CRM & Automation (Contextual Awareness):

• CRM Systems (e.g., Salesforce): Awareness of how customer data is managed and used within CRM systems can be relevant for designing client-facing data products.

• Marketing Automation Platforms: Understanding the workflows and data outputs of marketing automation tools can provide context for designing AI solutions in this space.

• Data Warehousing/Engineering Tools (e.g., Databricks): Familiarity with the context of data platforms like Databricks can help in designing interfaces that interact with or leverage data processed by such systems.

Collaboration & Project Management:

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

• Jira/Confluence: For project tracking, backlog management, and documentation, especially within an Agile development environment.

📝 Enhancement Note: The primary tool requirement is Figma. However, familiarity with data visualization and analytics platforms, as well as an understanding of enterprise CRM and data warehousing contexts, will be highly advantageous for designing effective AI products in the marketing and media analytics space.

👥 Team Culture & Values

Operations Values:

• Innovation & Future-Forward Thinking: Dentsu actively invests in and promotes innovative solutions, particularly in AI and data. This value will drive the team to explore new possibilities and push the boundaries of what's achievable.

• Collaboration & Partnership: The company emphasizes strong cross-functional teamwork. Operations professionals are expected to work seamlessly with engineering, product, sales, and client teams.

• Data-Driven Excellence: A commitment to using data to inform decisions, measure impact, and drive continuous improvement in both products and processes.

• Client Centricity: A core focus on understanding and meeting client needs, ensuring that products and services deliver tangible business value and drive client success.

• Continuous Learning & Adaptability: In the rapidly evolving fields of AI and marketing technology, a mindset of ongoing learning and adaptability is crucial for staying ahead.

Collaboration Style:

• Cross-Functional Integration: Expect a highly integrated approach where design, engineering, and product management work in tight sprints and feedback loops, sharing ownership and responsibility.

• Open Communication: A culture that encourages open dialogue, constructive feedback, and transparency across all levels and functions.

• Agile & Iterative: The team likely operates with an agile mindset, embracing iterative development, regular stand-ups, sprint reviews, and retrospectives to foster continuous improvement and adaptation.

• Knowledge Sharing: Opportunities to share learnings, best practices, and insights through internal presentations, documentation, and collaborative problem-solving sessions.

📝 Enhancement Note: The team culture at Dentsu, particularly within its AI product development groups, is expected to be dynamic, collaborative, and focused on innovation and data-driven results. Candidates should demonstrate a proactive, team-oriented approach aligned with these values.

⚡ Challenges & Growth Opportunities

Challenges:

• Translating Complex AI into Simplicity: The primary challenge will be to design intuitive user experiences for sophisticated AI systems (multi-agent systems, Genie spaces) that are not inherently user-friendly, catering to users with varying technical aptitudes.

• Balancing Innovation with Usability: Ensuring cutting-edge AI capabilities are accessible and practical, avoiding "over-engineering" or creating features that are too complex for the intended audience.

• Designing for Trust and Transparency: Building user confidence in AI systems by designing clear explanations of how the AI works, why it made certain decisions, and how users can intervene or correct it.

• Cross-Time Zone Collaboration: Effectively collaborating with distributed global teams, managing communication barriers, and ensuring alignment across different working hours.

• Rapidly Evolving AI Landscape: Keeping pace with the fast-moving developments in AI technology and integrating new capabilities into product designs while maintaining a coherent user experience.

Learning & Development Opportunities:

• Deep Dive into AI/ML Product Design: Gain specialized expertise in designing for advanced AI applications, including agentic systems and conversational AI.

• Mastery of Design Systems: Contribute to and refine sophisticated design systems for a large-scale product suite, enhancing skills in component-based design and governance.

• Industry Trends & Conferences: Opportunities to attend industry events, webinars, and conferences focused on AI, UX, and marketing technology to stay abreast of the latest trends.

• Mentorship & Leadership: Potential to mentor junior designers and grow into leadership roles, influencing design strategy and team development.

• Cross-Functional Skill Development: Opportunity to work closely with AI engineers and data scientists, deepening understanding of AI capabilities and data science principles.

📝 Enhancement Note: The challenges are inherent to working at the forefront of AI product development. The growth opportunities are significant, offering deep specialization in AI design and potential pathways into leadership within a global organization.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to design a user experience for a complex, multi-agent system. What were the key challenges, and how did you approach them?" (Focus on your process for understanding complexity, user needs, and mapping interactions.)

• "How do you approach designing for AI transparency and trust? Can you provide an example from your portfolio or a hypothetical scenario?" (Highlight your methods for explaining AI outputs and building user confidence.)

• "Imagine you need to design a conversational interface for data exploration for a client who is not technically savvy. Walk me through your design process and key considerations." (Demonstrate your ability to simplify complex data interaction and tailor solutions for specific user profiles.)

Company & Culture Questions:

• "What interests you about Dentsu and our work in AI product development?" (Research Dentsu's recent AI initiatives, case studies, and their overall vision.)

• "How do you approach working with distributed teams across different time zones?" (Discuss your strategies for asynchronous communication, documentation, and collaboration.)

• "Describe your experience working within an Agile development environment. How do you integrate design into Agile sprints?" (Showcase your understanding of Agile methodologies and your role within them.)

Portfolio Presentation Strategy:

• Structure Your Narrative: For each project, clearly define the problem, your role, the process, the solution, and the impact. Use a consistent framework.

• Emphasize Your AI/Data Design Thinking: Be prepared to articulate the specific considerations and challenges you addressed when designing for AI and complex data sets.

• Show, Don't Just Tell: Use visuals, interactive prototypes, and concise explanations to showcase your design solutions. Avoid lengthy theoretical discussions.

• Prepare for Deep Dives: Anticipate detailed questions about your design decisions, user research findings, and how you iterated based on feedback.

• Highlight Collaboration: Mention how you worked with stakeholders, engineers, and product managers throughout the process.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong understanding of AI product design challenges, a robust and iterative design process, excellent collaboration skills, and the ability to articulate the business impact of design decisions. Thorough research into Dentsu's AI initiatives will be key.

📌 Application Steps

To apply for this AI Product Designer position:

• Submit your comprehensive resume and a link to your online portfolio through the Dentsu careers portal.

• Portfolio Customization: Tailor your portfolio to highlight 2-3 key projects that best demonstrate your experience with AI/ML products, complex workflow design, data visualization, and enterprise UX. Ensure these projects showcase your end-to-end design process and impact.

• Resume Optimization: Refine your resume to clearly articulate your 5+ years of product design experience, emphasizing skills in Figma, AI product design, user research, and collaboration. Use keywords from the job description naturally.

• Prepare for Portfolio Presentation: Practice walking through your selected portfolio projects, focusing on telling a compelling story about the problem, your process, challenges, solutions, and outcomes. Be ready to discuss your design rationale in detail.

• Company Research: Thoroughly research Dentsu, Merkle, their AI initiatives, and recent work in the marketing technology space. Understand their company culture, values, and strategic direction to better align your responses during interviews.

⚠️ 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.