Lead Product Designer

📍 Job Overview

Job Title: Lead Product Designer

Company: Faculty

Location: London, England, United Kingdom

Job Type: FULL_TIME

Category: Product Design / AI / Life Sciences

Date Posted: 2026-04-14

Experience Level: Mid-Senior (5-10 years)

Remote Status: Hybrid

🚀 Role Summary

• Define and execute the design vision for Faculty's innovative Life Sciences products, leveraging AI/ML capabilities to address critical healthcare challenges.

• Lead comprehensive user research initiatives to deeply understand client ecosystems, map complex user workflows, and translate insights into robust, actionable design strategies.

• Drive cross-functional collaboration with engineering, product management, and delivery leads to ensure user needs are balanced with technical feasibility and strategic client objectives.

• Develop and evangelize best-in-class design methodologies to foster a culture of innovation, iterative development, and continuous validation within the Applied AI consulting group.

📈 Primary Responsibilities

• Spearhead the end-to-end design process for AI-powered Life Sciences products, from initial concept and user research through to high-fidelity prototypes and implementation oversight.

• Conduct in-depth user and stakeholder interviews, contextual inquiries, and usability testing to uncover unmet needs and validate design solutions within the complex Life Sciences domain.

• Translate complex business requirements and ambiguous user needs into clear, intuitive, and scalable design solutions, ensuring alignment with product roadmaps and client goals.

• Champion a user-centered design philosophy, advocating for user needs while effectively communicating design rationale and trade-offs to diverse audiences, including technical teams and senior stakeholders.

• Contribute to the development of reusable design patterns, component libraries, and design system frameworks to enhance efficiency and consistency across Faculty's product portfolio.

• Collaborate closely with data scientists and AI engineers to understand the nuances of AI/ML models and integrate them seamlessly into user-friendly product experiences.

• Facilitate design thinking workshops and brainstorming sessions to foster innovation and problem-solving within cross-functional teams.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong foundation in Design, Human-Computer Interaction (HCI), Computer Science, or a related field is highly advantageous. Equivalent practical experience will be considered.

Experience: A minimum of 5-10 years of professional experience in product design, with a significant focus on designing scalable software products, ideally those incorporating AI/ML technologies. Experience in a professional services, consulting, or agency environment is a strong plus, demonstrating adaptability across diverse clients and problem spaces.

Required Skills:

• Proven expertise in end-to-end product design, including user research, wireframing, prototyping, and usability testing.

• Demonstrable experience designing for complex software products, with a preference for those leveraging AI/ML.

• Strong portfolio showcasing impactful work that illustrates the ability to derive clarity from ambiguity and drive iterative design progress.

• Exceptional collaboration and communication skills, with the ability to work effectively in cross-functional teams and influence stakeholders.

• Experience in developing and evangelizing design methodologies and best practices.

• Ability to practice evidence-based design, articulating design choices clearly and credibly.

• Experience in user workflow mapping and translating research into actionable design strategies.

Preferred Skills:

• Direct experience or a demonstrable, strong interest in the Life Sciences sector (e.g., pharmaceuticals, biotechnology, healthcare technology).

• Experience working within a consulting or professional services firm, adapting to diverse client needs and project scopes.

• Familiarity with Agile development methodologies and working within fast-paced, iterative environments.

• Experience with design systems and fostering their adoption.

• Mentorship experience with junior designers.

• Understanding of technical constraints and feasibility related to AI/ML development.

📝 Enhancement Note: The role emphasizes end-to-end design leadership and methodology evangelism, suggesting a need for a candidate who can not only execute but also shape and elevate the design practice within the organization. The mention of "Applied AI consulting group" implies a blend of product thinking and client-facing advisory.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• A comprehensive portfolio is mandatory, showcasing a diverse range of impactful product design projects.

• Projects should demonstrate the ability to lead the entire design process, from initial problem definition and user research to final solution delivery and iteration.

• Clearly articulate your role and contributions within each project, especially in cross-functional team settings.

• Showcase your ability to derive clarity from ambiguous requirements and drive iterative progress toward impactful outcomes.

• Include examples of how you've translated user needs and business objectives into effective design solutions.

Process Documentation:

• Be prepared to discuss your personal design methodologies and how you contribute to evolving team-wide design practices.

• Demonstrate experience in building and evangelizing design methodologies that contribute to repeatable propositions and value for the wider team.

• Showcase examples of how you foster innovation through iterative processes and validation.

• Be ready to explain how you practice evidence-based design and articulate your choices credibly to both internal and external stakeholders.

📝 Enhancement Note: The requirement for a portfolio demonstrating "end-to-end design process" and "deriving clarity from ambiguous requirements" points to a need for a candidate who is not just a skilled executor but also a strategic thinker capable of navigating complex problems and influencing outcomes.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Lead Product Designers in London with 5-10 years of experience, particularly in tech/AI companies, the estimated salary range is £70,000 - £100,000 per annum. This range can vary based on the candidate's specific experience, skill set, and performance during the interview process.

Benefits:

• Unlimited Annual Leave Policy: Offers significant flexibility and trust in managing personal time off.

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

• Enhanced Parental Leave: Generous provisions for new parents, supporting work-life balance during significant life events.

• Family-Friendly Flexibility & Flexible Working: A commitment to supporting employees with family responsibilities and offering adaptable work arrangements.

• Sanctus Coaching: Access to professional coaching services for personal and professional development.

• Hybrid Working: A structured approach that combines in-office collaboration with remote flexibility.

Working Hours: While the standard full-time work week is typically 40 hours, Faculty emphasizes flexibility. The specific schedule can be discussed, aligning with hybrid working policies and the need for effective collaboration with global clients and teams.

📝 Enhancement Note: The salary estimate is based on average compensation data for Lead Product Designer roles in London's tech sector, considering the company's industry (AI, consulting) and the specified experience level. Benefits are directly listed from the job description, highlighting Faculty's commitment to employee well-being and flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Faculty operates within the Applied Artificial Intelligence (AI) and Machine Learning (ML) sector, with a specific focus on consulting and product development for enterprise clients. The Life Sciences team specializes in building AI solutions for the pharmaceutical, biotechnology, and healthcare industries.

Company Size: Faculty is a growing company, likely in the scale-up phase, employing between 50-250 individuals. This size indicates a dynamic environment with opportunities for significant individual impact and cross-functional collaboration, while still maintaining a cohesive culture.

Founded: Faculty was established in 2014, giving it over a decade of experience in the rapidly evolving AI landscape. This longevity suggests a stable, experienced organization with a proven track record and deep technical expertise.

Team Structure:

• The Life Sciences team is a specialized unit within Faculty, focused on delivering AI solutions for major pharma firms, academic research centers, and MedTech startups.

• The Product Design function likely comprises a mix of individual contributors and potentially junior designers, with this Lead role overseeing and mentoring them.

• Reporting lines would typically place the Lead Product Designer under a Head of Product, Head of Design, or a senior Product Manager, with close collaboration across Engineering, Data Science, and Delivery Leads.

Methodology:

• Faculty emphasizes a human-centric approach to AI, focusing on responsible innovation and deploying AI solutions that create measurable, positive impact.

• Design methodologies are likely iterative, evidence-based, and focused on understanding complex user workflows and client ecosystems.

• The company encourages a culture of innovation, leveraging cross-functional expertise and fostering open communication.

• Data-driven decision-making and a focus on translating technical capabilities into tangible business value are likely core to their approach.

Company Website: https://faculty.ai

📝 Enhancement Note: Faculty's positioning as an Applied AI consultancy, particularly within Life Sciences, suggests a blend of deep technical expertise, client-facing advisory, and product development. The company's founding date indicates maturity in a fast-moving field.

📈 Career & Growth Analysis

Operations Career Level: This Lead Product Designer role represents a senior individual contributor (IC) or a potential leadership track position. It signifies a move beyond pure execution into strategic design vision, methodology development, and team mentorship. The role is critical for shaping the product experience within a high-impact sector.

Reporting Structure: The Lead Product Designer will likely report to a Director or Head of Product/Design. They will work closely with Product Managers, Engineering Leads, and Delivery Leads, forming core project teams. Mentoring junior designers is a key aspect, suggesting a leadership component within the design function.

Operations Impact: The "Lead Product Designer" title, especially within an AI consulting firm like Faculty, implies a significant impact on revenue generation and strategic client success. By defining and executing the design vision for Life Sciences products, this role directly influences the adoption, effectiveness, and perceived value of Faculty's AI solutions. This, in turn, drives client satisfaction, repeat business, and the company's reputation in a critical market.

Growth Opportunities:

• Leadership Track: Potential to grow into a Head of Design or a similar leadership role, managing larger design teams and setting broader design strategy for Faculty.

• Specialization: Deepen expertise in AI/ML product design within the Life Sciences sector, becoming a go-to expert for complex challenges in this domain.

• Methodology Development: Lead initiatives to refine and expand Faculty's design processes, systems, and best practices, influencing how the entire organization approaches product design.

• Client Advisory: Develop skills in client relationship management and consultative selling, leveraging design expertise to advise senior client stakeholders on AI strategy and product innovation.

• Broader Product Scope: Potentially transition to overseeing design for a wider range of Faculty's AI products beyond Life Sciences.

📝 Enhancement Note: The "Lead" designation points to a role with significant autonomy, strategic input, and mentorship responsibilities, offering a clear path for career advancement within Faculty's growing AI consulting practice.

🌐 Work Environment

Office Type: Faculty operates on a hybrid working model, indicating a blend of in-office collaboration and remote work. The office environment is likely designed to foster collaboration, innovation, and focused work.

Office Location(s): The role is based in London, England. Specific office details would typically be available upon inquiry or during the interview process, but London offers a vibrant tech ecosystem and excellent connectivity.

Workspace Context:

• Collaborative Environment: The hybrid model and emphasis on cross-functional work suggest an office space that facilitates team meetings, brainstorming sessions, and knowledge sharing. Expect a modern, tech-enabled workspace.

• Operations Tools & Technology: Access to industry-standard design tools (Figma, Sketch, etc.), collaboration platforms (Slack, Teams), and potentially internal knowledge bases or design systems.

• Team Interaction: Opportunities for regular interaction with a diverse team of product managers, engineers, data scientists, delivery leads, and fellow designers, fostering a dynamic and intellectually stimulating atmosphere.

Work Schedule: Faculty offers flexible working arrangements. While a standard 40-hour week is typical for full-time roles, the emphasis on "Family-Friendly Flexibility" and "Unlimited Annual Leave" suggests a results-oriented culture that prioritizes outcomes over strict hours, allowing for adaptation to personal needs and project demands.

📝 Enhancement Note: The hybrid model and flexible working policies indicate a modern, employee-centric approach to work, balancing the benefits of in-person collaboration with the autonomy of remote work.

📄 Application & Portfolio Review Process

Interview Process:

1. Application & Portfolio Submission: Initial review of your CV and, critically, your portfolio. The portfolio is your primary tool to showcase your capabilities.

2. Recruiter Screening: A call with a recruiter to discuss your background, motivations, experience, and suitability for the role and Faculty's culture.

3. Hiring Manager Interview: A deeper dive with the hiring manager (likely a Head of Product or Design) focusing on your design philosophy, strategic thinking, leadership potential, and specific experience related to AI/ML and Life Sciences.

4. Design Challenge / Case Study Presentation: You will likely be asked to present a case study from your portfolio or tackle a hypothetical design problem. This assesses your end-to-end design process, problem-solving skills, and ability to articulate your rationale.

5. Cross-functional Team Interview: An opportunity to meet with potential peers (e.g., Product Managers, Engineers) to assess collaboration style, communication skills, and ability to integrate into the team.

6. Final Interview / Leadership Discussion: Potentially a conversation with a senior leader to discuss your overall fit with Faculty's vision, values, and long-term growth potential.

Portfolio Review Tips:

• Curate Strategically: Select 3-4 of your most impactful projects that best demonstrate your end-to-end design process, particularly those involving complex software, AI/ML, or ideally, the Life Sciences sector.

• Tell a Story: For each project, clearly outline the problem, your role and process, the challenges you faced, your design decisions, the solutions you created, and the measurable impact or outcomes. Use visuals effectively.

• Highlight Ambiguity Navigation: Emphasize how you tackled projects with unclear requirements or complex problem spaces, showcasing your ability to bring order and clarity.

• Showcase AI/ML Understanding: If possible, include projects that demonstrate your understanding of designing for AI/ML products, even if it's conceptual.

• Demonstrate Collaboration: Explicitly mention how you worked with cross-functional teams (engineers, PMs, stakeholders) and how you communicated your design choices.

• Focus on Impact: Quantify the results of your design work whenever possible (e.g., increased user engagement, improved efficiency, successful product launch).

Challenge Preparation:

• Understand the Context: If given a case study, thoroughly research Faculty, the Life Sciences sector, and common AI applications in healthcare.

• Structure Your Approach: Clearly define the problem, your assumptions, your research methods (even if hypothetical), your design process, key decisions, and proposed solutions.

• Articulate Trade-offs: Be prepared to discuss the trade-offs inherent in design decisions, considering user needs, technical feasibility, and business goals.

• Practice Presentation: Rehearse your presentation to ensure clarity, conciseness, and confidence. Be ready to answer questions and engage in a discussion about your approach.

📝 Enhancement Note: The emphasis on a portfolio and case study presentation is standard for senior design roles, particularly in consulting-oriented firms. Candidates should prepare to articulate not just design execution but strategic thinking and process.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping: Figma (highly probable given industry trends), Sketch, Adobe Creative Suite (Illustrator, Photoshop).

• Collaboration & Communication: Slack, Microsoft Teams, Zoom, Google Workspace.

• Project Management: Jira, Asana, Trello (or similar tools used by cross-functional teams).

Analytics & Reporting:

• Tools for user analytics (e.g., Google Analytics, Mixpanel, Amplitude) to understand user behavior and product performance.

• Potentially tools for A/B testing and experimentation to validate design changes.

CRM & Automation:

• While not directly a designer's tool, understanding how CRM systems (like Salesforce) and marketing automation platforms impact user journeys and data can be beneficial.

• Familiarity with data platforms and how AI/ML models are integrated into workflows is essential.

📝 Enhancement Note: The technology stack reflects typical tools used in modern product design and agile development environments, with a specific emphasis on AI/ML integration within the Life Sciences context.

👥 Team Culture & Values

Operations Values:

• Intellectual Curiosity: A deep desire to learn, explore complex problems, and understand the "why" behind user needs and business challenges.

• Desire for Impact: A drive to build and deploy responsible AI solutions that create measurable positive change for clients and society, particularly in critical sectors like Life Sciences.

• Collaboration & Openness: A commitment to working openly across disciplines, leveraging diverse expertise, and bringing others along on the design and development journey.

• Seeking Truth & Diversity: Valuing diverse perspectives to foster robust thinking and ensure solutions are relevant and equitable. Faculty actively encourages applications from all backgrounds.

• Innovation & Responsibility: A focus on pushing the boundaries of AI while ensuring ethical and responsible application.

Collaboration Style:

• Cross-functional Integration: Designers are expected to be embedded within cross-functional teams, working closely with Product Managers, Engineers, and Data Scientists from inception to delivery.

• Process Review & Feedback: A culture that encourages open feedback loops, constructive critique, and continuous improvement of design processes and outcomes.

• Knowledge Sharing: Active participation in sharing insights, best practices, and learnings across the design and broader Faculty community.

• Evidence-Based Approach: Decisions are driven by data, user research, and logical reasoning, fostering a culture of credibility and trust.

📝 Enhancement Note: Faculty's values emphasize intellectual rigor, a commitment to positive impact through AI, and a strong belief in diversity and collaboration, all crucial for success in a complex, client-facing AI consultancy.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating Ambiguity in Life Sciences: The Life Sciences sector is highly regulated and complex. Translating diverse client needs and intricate scientific workflows into user-friendly AI products will be a significant challenge.

• Designing for AI/ML Nuances: Effectively designing user experiences that account for the probabilistic nature, potential biases, and evolving capabilities of AI/ML models requires a nuanced approach.

• Balancing User Needs with Technical Feasibility & Client Goals: As a consultant, you'll need to expertly balance the ideal user experience with project constraints, client expectations, and the underlying technical architecture.

• Evangelizing Design Best Practices: Building and embedding new design methodologies across a growing organization requires strong influence, communication, and change management skills.

Learning & Development Opportunities:

• Deep Dive into Life Sciences AI: Immerse yourself in a critical and rapidly advancing field, understanding its unique challenges and opportunities for AI application.

• Advanced AI/ML Product Design: Enhance your expertise in designing for cutting-edge AI/ML technologies and complex data environments.

• Consulting & Client Advisory Skills: Develop skills in stakeholder management, client communication, and consultative problem-solving within a professional services context.

• Leadership & Mentorship: Gain experience in leading design initiatives, mentoring junior talent, and contributing to the strategic direction of the design function.

• Industry Conferences & Certifications: Opportunities to attend relevant industry events and pursue certifications to stay at the forefront of AI, design, and Life Sciences innovation.

📝 Enhancement Note: The challenges are inherently tied to the company's domain (AI consultancy in Life Sciences), offering significant opportunities for professional growth by tackling complex, high-impact problems.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to define a design vision for a product with unclear initial requirements. How did you approach it, and what was the outcome?" (Focus on your process for bringing clarity and driving iterative progress.)

• "How do you balance user needs with technical feasibility and client business goals, especially in a consulting context?" (Highlight your negotiation, communication, and trade-off analysis skills.)

• "Walk us through a complex user workflow you've mapped. What tools and methods did you use, and how did it inform your design decisions?" (Demonstrate your research and analytical capabilities.)

Company & Culture Questions:

• "Why are you interested in Faculty and our Life Sciences team specifically?" (Research Faculty's mission, impact, and the specifics of the Life Sciences team's work.)

• "How do you ensure your design choices are evidence-based and credible to both technical teams and non-technical stakeholders?" (Discuss your methods for validation and communication.)

Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly define the problem, your role, your process (research, ideation, iteration, validation), key decisions, and the measurable impact.

• Emphasize Your Process: Show how you think and work, not just the final screens. Discuss the trade-offs you made and why.

• Highlight AI/ML Relevance: If you have projects involving AI/ML, explain the specific design considerations for those technologies.

• Be Ready for Questions: Anticipate deep dives into your design choices, challenges, and how you handle feedback.

• Connect to Faculty: Where possible, subtly tie your experiences and thinking to Faculty's mission and the Life Sciences domain.

📝 Enhancement Note: Interview preparation should focus on demonstrating strategic thinking, robust design process, strong collaboration skills, and a clear understanding of Faculty's context in AI consulting for Life Sciences.

📌 Application Steps

To apply for this Lead Product Designer position:

• Submit your application via the provided link on Ashby, ensuring your CV and a compelling portfolio are uploaded.

• Portfolio Customization: Tailor your portfolio to highlight projects demonstrating end-to-end design leadership, AI/ML experience, and ideally, any work within complex or regulated industries like Life Sciences. Focus on showcasing your ability to derive clarity from ambiguity.

• Resume Optimization: Ensure your resume clearly articulates your 5-10 years of experience, highlighting achievements related to product strategy, user research, cross-functional collaboration, and methodology development. Use keywords from the job description.

• Interview Preparation: Thoroughly research Faculty, their work in Life Sciences, and their company values. Prepare detailed case studies from your portfolio to present and practice articulating your design process and rationale for potential challenges.

• Company Research: Understand Faculty's mission to use AI for positive impact. Research their recent projects and their approach to responsible AI. Consider how your skills and passion align with their specific focus on the Life Sciences sector.

⚠️ 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.

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