Senior Product Designer

📍 Job Overview

Job Title: Senior Product Designer

Company: Faculty

Location: London, England, United Kingdom

Job Type: FULL_TIME

Category: Product Design / AI Native Solutions

Date Posted: 2026-05-19

Experience Level: 5-10 Years

🚀 Role Summary

• Lead the design of bespoke, AI-native solutions for clients, focusing on the Energy, Transition, and Environment sectors.

• Drive strategic design decisions through autonomous user research and synthesis of insights.

• Own the end-to-end delivery of wireframes, prototypes, and detailed designs for complex, high-impact user interfaces.

• Evolve and maintain the company's design system, ensuring consistency and scalability across projects.

• Foster cross-functional collaboration and effectively communicate design rationale to senior leadership and clients.

📝 Enhancement Note: This role is specifically for a Senior Product Designer with a focus on AI-native products within the energy transition sector. The "Senior" designation implies a need for leadership in design practice, mentoring, and strategic influence, extending beyond individual project contributions. The emphasis on "AI-native" suggests a need for understanding how AI capabilities shape user experiences and product functionality.

📈 Primary Responsibilities

• Spearhead the creation of complex, high-impact user interfaces that adhere to rigorous accessibility and inclusion standards.

• Plan, conduct, and oversee autonomous user research to uncover critical insights that inform strategic design decisions and product direction.

• Take ownership of the entire design lifecycle, from initial concept through to final delivery of wireframes, prototypes, and detailed design specifications for challenging problems.

• Drive the evolution and maintenance of the organizational design system, ensuring it meets evolving project and company needs, and provide strategic implementation guidance to engineering and design peers.

• Facilitate seamless cross-functional collaboration among machine learning engineers, data scientists, and software engineers, and articulate design rationale clearly to diverse stakeholders, including senior leadership and external clients.

• Lead and champion iterative design processes, encouraging experimentation and validation efforts to continuously enhance product usability and user satisfaction.

• Mentor junior designers and contribute to building the overall design capability and systems within Faculty.

📝 Enhancement Note: The responsibilities highlight a blend of hands-on design execution, strategic thinking, and leadership. The emphasis on "autonomous user research" and "evolving the design system" indicates a need for a proactive and self-directed individual who can shape processes and best practices, not just follow them. The mention of "AI-native" solutions implies a requirement to understand and design for machine learning-driven functionalities.

🎓 Skills & Qualifications

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

Experience: 5-10 years of professional experience in product design, with a significant portion focused on designing and shipping AI-native products at scale. Experience in a consulting services environment is highly desirable.

Required Skills:

• Proven experience designing and shipping AI-native products at scale.

• Demonstrated ability to influence product direction and broader product strategy.

• Strong leadership in iterative design processes, including user research, wireframing, prototyping, and detailed UI design.

• Advanced expertise in design tools and methods, with the ability to create high-quality user experiences.

• Excellent collaboration and communication skills, with a proven ability to facilitate cross-functional teamwork and clearly articulate design rationale to diverse stakeholders.

• Experience in establishing and evolving design systems, ensuring consistency and scalability.

Preferred Skills:

• Experience working within a consulting services environment.

• Familiarity with AI tools and technologies relevant to design.

• Experience mentoring junior designers and contributing to design team growth.

• Background in the Energy, Transition, or Environment sectors.

📝 Enhancement Note: The experience level (5-10 years) suggests a need for a candidate who can operate independently and take on significant responsibility. The "ideal" consulting experience points towards a candidate comfortable with client-facing work, project-based engagements, and delivering solutions within defined timelines and scopes. The emphasis on influencing product strategy and contributing beyond immediate projects highlights the senior nature of the role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase a minimum of 2-3 complex, end-to-end design projects, with at least one prominently featuring an AI-native product.

• Clearly articulate your role and contributions within each project, especially regarding strategic influence and leadership.

• Demonstrate proficiency in user research methodologies, including planning, execution, and synthesis of insights that led to design decisions.

• Provide detailed examples of wireframes, interactive prototypes, and final UI designs, emphasizing problem-solving and user-centricity.

• Include case studies that illustrate how you've contributed to or evolved a design system, highlighting its impact on consistency and scalability.

• Present evidence of successful collaboration with cross-functional teams (ML engineers, data scientists, software engineers) and how you communicated design rationale to stakeholders.

Process Documentation:

• Detail your approach to planning and executing autonomous user research initiatives, including participant recruitment and ethical considerations.

• Explain your methodology for iterative design and validation, including A/B testing, usability testing, and feedback incorporation.

• Illustrate your process for contributing to and evolving design systems, including version control, documentation, and governance.

• Describe how you facilitate cross-functional collaboration and manage design critiques within a team environment.

📝 Enhancement Note: For a Senior Product Designer role, the portfolio is critical. It needs to go beyond just showcasing visually appealing designs and demonstrate strategic thinking, leadership, and a deep understanding of the design process, particularly for complex, AI-driven products. The emphasis on "shipping at scale" and "influencing product strategy" means the portfolio should highlight impact and strategic contributions, not just the aesthetics or functionality of the final product.

💵 Compensation & Benefits

Salary Range: £70,000 - £95,000 per annum (estimated based on Senior Product Designer roles in London with experience in AI/Tech sectors).

Benefits:

• Unlimited Annual Leave Policy: Offers flexibility and promotes work-life balance, allowing employees to take time off as needed.

• Private Healthcare and Dental: Comprehensive medical coverage for employees and potentially their families.

• Enhanced Parental Leave: Provides extended paid leave for new parents, supporting family well-being.

• Family-Friendly Flexibility & Flexible Working: Accommodates diverse personal needs and promotes a healthy work-life integration.

• Sanctus Coaching: Access to professional coaching for mental well-being and personal development.

• Hybrid Working: Combines the benefits of in-office collaboration with remote flexibility.

Working Hours: Standard 40 hours per week, with flexibility offered through the hybrid working model and unlimited annual leave policy.

📝 Enhancement Note: The salary range is estimated for a Senior Product Designer in London, considering the company's industry (AI, Tech) and the role's seniority and specific focus (AI-native, consulting). This range is benchmarked against similar roles in the UK tech market, factoring in the cost of living in London. The benefits listed are directly extracted from the provided text and are highlighted as attractive perks for operations professionals seeking a supportive work environment.

🎯 Team & Company Context

🏢 Company Culture

Industry: Artificial Intelligence (AI), Technology Consulting, Clean Energy Solutions. Faculty leverages AI to drive performance transformation for over 350 global clients across various sectors including government, finance, retail, energy, life sciences, and defense. The Energy, Transition, and Environment business unit specifically focuses on accelerating the transition to net-zero emissions and driving efficiencies in the utility sector.

Company Size: Faculty is a growing company, indicated by its work with over 350 global customers and its continuous search for new talent. While an exact number isn't provided, the scope of their client base and the mention of building design capability suggests a medium-to-large sized organization with a significant technical and consulting workforce.

Founded: Faculty was established in 2014 with the vision that AI would be a transformative technology. This foundational belief drives their innovation and deployment of responsible AI solutions.

Team Structure:

• The role sits within the Energy, Transition, and Environment business unit, which is dedicated to pioneering change in the clean energy revolution.

• The Senior Product Designer will work closely with expert machine learning engineers, data scientists, and software engineers, indicating a highly technical and collaborative environment.

Methodology:

• Human-Centric AI: Faculty emphasizes the responsible and intelligent deployment of AI, focusing on human-centric solutions that deliver measurable impact.

• Data-Driven Impact: The company's success is built on delivering tangible results for clients, driven by deep technical, product, and delivery expertise.

• Innovation and Responsibility: Faculty balances innovation with a commitment to responsible AI development, ensuring ethical considerations are integrated into their work.

• Cross-functional Collaboration: The nature of AI-native solutions necessitates close collaboration between design, engineering, and data science teams.

Company Website: https://faculty.ai

📝 Enhancement Note: The company culture is characterized by intellectual curiosity, a drive for positive legacy through technology, and a commitment to responsible AI. The specific business unit context (Energy, Transition, Environment) means candidates should be interested in sustainability and clean energy challenges. The "senior" aspect of the role implies a culture that values mentorship and the development of internal best practices.

📈 Career & Growth Analysis

Operations Career Level: Senior Product Designer. This level signifies a seasoned professional expected to lead design initiatives, mentor others, and contribute to strategic product decisions. The role demands not just execution but also thought leadership in design practice, particularly within the complex domain of AI-native solutions for critical industries like clean energy.

Reporting Structure: While not explicitly detailed, a Senior Product Designer typically reports to a Head of Design, Design Manager, or a Product Lead. They are expected to work closely with cross-functional teams (ML Engineers, Data Scientists, Software Engineers) and present to senior leadership and clients, indicating a significant level of autonomy and influence.

Operations Impact: The Senior Product Designer will have a direct impact on the success of AI-native solutions delivered to clients in the crucial Energy, Transition, and Environment sector. By creating intuitive, impactful, and user-centric interfaces, they will enable clients to leverage AI for achieving net-zero emissions goals and driving operational efficiencies. Their work will contribute to Faculty's reputation for delivering exceptional technical and product expertise in a rapidly evolving field.

Growth Opportunities:

• Design Leadership: Opportunity to shape and grow Faculty's design capability, establish best practices, and potentially lead design efforts for major client engagements.

• Specialization: Deepen expertise in designing for AI-native products and gain specialized knowledge within the clean energy and sustainability sectors.

• Mentorship: Guide and mentor junior designers, fostering their development and contributing to a strong design culture.

• Strategic Influence: Influence product strategy and client roadmaps through compelling design thinking and user advocacy.

• Cross-functional Expertise: Enhance collaboration skills with world-class ML engineers, data scientists, and software engineers, broadening understanding of AI development.

📝 Enhancement Note: The "Senior" title, coupled with responsibilities like "share best practice across the organisation" and "build the design capability," suggests significant growth potential beyond individual contributor roles. This could lead to Design Lead, Head of Design, or Product Management roles within Faculty, especially given the company's growth trajectory and focus on innovation.

🌐 Work Environment

Office Type: Faculty operates a hybrid working model. This means the role is not fully remote, requiring some in-office presence for collaboration, but also allowing for remote work flexibility. The office environment is likely to be modern, collaborative, and conducive to technology and innovation-focused work.

Office Location(s): The primary location is London, England. Specific office details are not provided, but given the hybrid nature, it implies a central London location accessible for employees working in the region.

Workspace Context:

• Collaborative Hub: The office serves as a space for focused work, team collaboration, brainstorming sessions, and client interactions. Expect dynamic team environments where cross-functional teams work together.

• Technology-Rich: As an AI and technology company, the workspace will be equipped with modern tools and technologies essential for design and development.

• Inspiration and Innovation: The environment is designed to foster intellectual curiosity and innovation, aligning with Faculty's mission to leverage AI for positive impact.

Work Schedule: While the standard is 40 hours per week, the "Family-Friendly Flexibility" and "Unlimited Annual Leave Policy" suggest a culture that prioritizes work-life balance and employee well-being, allowing for adaptable scheduling where feasible.

📝 Enhancement Note: The hybrid model implies a need for candidates who can manage their time effectively, balancing focused remote work with collaborative in-office sessions. The mention of "Family-Friendly Flexibility" suggests a supportive environment for employees with family commitments.

📄 Application & Portfolio Review Process

Interview Process:

1. Talent Team Screen (40 minutes): An initial screening call to assess cultural fit, basic qualifications, and understanding of the role. Be prepared to discuss your career path, motivation for applying to Faculty, and your general experience with AI-native products.

2. Portfolio Review (60 minutes): A deep dive into your design portfolio. Prepare to walk through 2-3 key projects, highlighting your process, problem-solving approach, strategic contributions, and the impact of your designs, especially those involving AI. Focus on the "why" and "how" behind your design decisions.

3. Case Study Interview (60 minutes): This typically involves a design challenge, either pre-assigned or conducted live. Focus on demonstrating your end-to-end design process, including research, ideation, iteration, and justification of your solutions. Expect this to be heavily focused on your ability to tackle complex problems in AI and potentially within the energy sector.

4. Meet the Team (30 minutes): An opportunity to connect with potential colleagues, including ML engineers, data scientists, and other designers. This is a chance to assess team fit and for them to evaluate your collaborative and communication skills. Prepare questions about team dynamics, workflows, and current projects.

Portfolio Review Tips:

• Curate Strategically: Select projects that best showcase your experience with AI-native products, complex UIs, design systems, and strategic influence.

• Tell a Story: For each project, clearly articulate the problem, your role, your process, the challenges faced, your solutions, and the outcomes. Use visuals effectively.

• Highlight AI Nuances: Emphasize how your design approach specifically addresses the unique challenges and opportunities of AI-driven products (e.g., explainability, trust, data visualization).

• Quantify Impact: Wherever possible, use metrics to demonstrate the success of your designs (e.g., user satisfaction improvements, efficiency gains, adoption rates).

• Be Ready to Defend Decisions: Understand the rationale behind every design choice and be prepared to discuss trade-offs and alternative solutions.

Challenge Preparation:

• Understand the Context: If given a pre-assigned case study, thoroughly research Faculty, their work in the Energy/Transition/Environment sector, and common challenges in AI deployment.

• Process Over Perfection: Focus on demonstrating a robust design process rather than a perfectly polished final solution. Show your thinking.

• Embrace Ambiguity: AI problems can be complex and ill-defined. Show how you approach ambiguity and break down problems.

• Collaborate: If it's a live exercise, engage with the interviewer(s) as if they were your team. Ask clarifying questions and articulate your thought process.

• Presentation Skills: Practice presenting your findings and solutions concisely and persuasively, tailored to a senior audience.

📝 Enhancement Note: The interview process is structured to assess a candidate's technical skills, strategic thinking, collaborative abilities, and cultural fit. The portfolio review and case study are critical for demonstrating hands-on expertise and problem-solving capabilities, especially in the specialized area of AI-native design.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping Software: Proficiency in industry-standard tools such as Figma, Sketch, Adobe Creative Suite (Illustrator, Photoshop), and prototyping tools like InVision or Axure is expected.

• AI Design Tools: Familiarity with or ability to quickly learn AI-assisted design tools and platforms that can enhance the design workflow.

• Wireframing & Flow Tools: Tools for creating detailed user flows, wireframes, and information architecture.

Analytics & Reporting:

• User Research Platforms: Experience with tools for conducting user interviews, surveys, and usability testing (e.g., UserTesting.com, Maze, SurveyMonkey).

• Data Visualization Tools: Understanding of how to work with data visualization principles and potentially tools that integrate with client data sources to inform design.

CRM & Automation:

• Collaboration & Project Management Tools: Experience with tools like Jira, Asana, Trello, or similar for managing design tasks and collaborating with engineering teams.

• Design System Management Tools: Familiarity with platforms or methodologies for managing and documenting design systems.

📝 Enhancement Note: While specific tools aren't listed, the role implies a need for expertise in the full suite of modern product design tools. The emphasis on "AI-native" suggests that any experience with AI-powered design assistants or platforms that facilitate the design of AI-driven features would be a significant advantage.

👥 Team Culture & Values

Operations Values:

• Intellectual Curiosity: A deep desire to understand complex problems and explore innovative solutions, particularly in the AI space.

• Desire for Positive Legacy: A drive to use technology for measurable, positive impact, aligning with Faculty's mission in clean energy and societal advancement.

• Seeking Truth: A commitment to rigorous analysis and data-driven decision-making, fostering an environment of intellectual honesty.

• Diversity of Thought: Valuing diverse backgrounds, perspectives, and experiences to strengthen problem-solving and innovation.

• Responsibility: A focus on developing and deploying AI responsibly, considering ethical implications and user trust.

Collaboration Style:

• Cross-functional Integration: Seamless collaboration between design, machine learning engineering, data science, and software engineering teams is paramount.

• Open Communication: A culture of clear, transparent communication, where design rationale is effectively articulated and feedback is actively sought and given.

• Mentorship & Knowledge Sharing: Senior members are expected to mentor and share best practices, fostering a culture of continuous learning and development within the design team and across the organization.

• Client-Focused: A strong orientation towards understanding client needs and delivering solutions that provide measurable impact.

📝 Enhancement Note: The values emphasize a blend of intellectual rigor, ethical considerations, and a passion for impactful technology. The collaboration style is highly integrated, requiring designers to be comfortable working closely with technical experts and client stakeholders.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for AI Complexity: Translating complex AI capabilities into intuitive and user-friendly interfaces requires deep understanding and creative problem-solving.

• Client-Specific Solutions: Developing bespoke AI-native solutions for diverse clients in the energy sector means adapting to unique business needs and technical constraints.

• Balancing Innovation with Responsibility: Ensuring AI solutions are not only cutting-edge but also ethical, explainable, and trustworthy.

• Evolving Design Systems: Continuously updating and scaling design systems to support a growing portfolio of AI-driven products.

• Influencing Stakeholders: Effectively communicating complex design concepts and advocating for user needs with both technical teams and non-technical clients/leadership.

Learning & Development Opportunities:

• AI & ML Specialization: Deepen expertise in the unique design challenges and opportunities presented by AI and machine learning applications.

• Clean Energy Sector Expertise: Gain in-depth knowledge of the clean energy transition, utility operations, and sustainability challenges.

• Design System Leadership: Develop advanced skills in building, managing, and scaling design systems for complex technological products.

• Client Engagement & Consulting Skills: Enhance abilities in client management, strategic advising, and delivering high-impact consulting engagements.

• Mentorship and Team Building: Opportunities to lead and mentor design talent, contributing to Faculty's overall design maturity.

📝 Enhancement Note: The challenges are inherent to working with cutting-edge technology and in a consulting capacity. The growth opportunities are significant, offering a chance to become a recognized expert in a high-demand field.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you led the design of an AI-native product from concept to launch. What were the key challenges and how did you overcome them?" (Focus on process, AI specifics, and impact).

• "How do you approach user research for complex AI systems where user intuition might be limited?" (Highlight your methodology for uncovering needs and validating designs).

• "How would you contribute to evolving Faculty's design system to better support AI-native products?" (Demonstrate understanding of design systems and AI integration).

• "Imagine you need to explain the rationale behind a complex AI-driven UI decision to a non-technical client. How would you approach this?" (Showcase your communication and stakeholder management skills).

Company & Culture Questions:

• "What interests you specifically about Faculty's work in the Energy, Transition, and Environment sector?" (Research their impact and align your interests).

• "How do you embody Faculty's values of intellectual curiosity and positive legacy in your design work?" (Provide specific examples).

• "Describe your experience working in a hybrid or consulting environment. What are your strategies for effective collaboration?" (Highlight adaptability and teamwork).

Portfolio Presentation Strategy:

• Narrative Flow: Structure your portfolio presentation around a clear narrative for each project – problem, approach, solution, and outcome.

• Visual Storytelling: Use high-fidelity mockups, prototypes, and relevant research artifacts to visually communicate your design process and decisions.

• Highlight AI Elements: Clearly call out where and how AI influenced your design choices, user flows, or product functionality.

• Quantify Impact: Present metrics and user feedback that demonstrate the success and value of your designs.

• Be Concise and Engaging: Respect the time limit, be articulate, and maintain an engaging presence. Anticipate questions and prepare thoughtful answers.

📝 Enhancement Note: Preparation should focus on demonstrating not just design skills but also strategic thinking, leadership potential, and an understanding of Faculty's specific domain (AI, energy transition). The portfolio and case study are the primary vehicles for showcasing these capabilities.

📌 Application Steps

To apply for this Senior Product Designer position:

• Submit your application through the provided link on Ashby.

• Tailor your resume: Highlight experience with AI-native products, shipping at scale, design systems, user research, and any consulting background. Use keywords from the job description.

• Curate your portfolio: Ensure it prominently features 2-3 strong projects showcasing your end-to-end design process, strategic contributions, AI product experience, and quantifiable impact. Prepare to present this effectively.

• Research Faculty: Understand their mission, their work in the Energy, Transition, and Environment sector, and their commitment to responsible AI.

• Prepare for the interview process: Practice articulating your design rationale, problem-solving approach, and leadership capabilities, especially in the context of AI and client 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.