Principal AI Content Designer, Wise Assistant

📍 Job Overview

Job Title: Principal AI Content Designer, Wise Assistant

Company: Wise

Location: London, England, United Kingdom

Job Type: Full-time

Category: AI / Conversational Design / Content Design

Date Posted: 2026-09-23

Experience Level: Senior / Principal (10+ years implied)

Remote Status: On-site

🚀 Role Summary

• Spearhead the design and architecture of AI-driven conversational experiences for the Wise Assistant, directly impacting customer support and product interaction.

• Drive the end-to-end automation strategy for a product squad, defining vision, setting quality standards, and ensuring impactful project delivery.

• Collaborate extensively with cross-functional teams including engineers, product managers, and data scientists to translate complex AI capabilities into intuitive and effective customer solutions.

• Champion design maturity and best practices in context engineering and AI systems, influencing and coaching other designers within the organization.

📝 Enhancement Note: This role is positioned as a Principal level, indicating a high degree of autonomy, strategic influence, and the expectation of mentoring and leadership within the AI design space. The focus on "Wise Assistant" suggests a primary application in customer support automation, but with potential for broader integration across the Wise product suite. The "Content Design Guild" affiliation highlights a community of practice for shared learning and development in AI-driven design.

📈 Primary Responsibilities

• Architect and design conversational AI systems, defining agent behavior, prompt engineering strategies, and the utilization of context and knowledge to resolve customer issues effectively.

• Collaborate with engineering, data science, and product teams to set the strategic direction for AI-powered customer assistance and coach these teams on execution.

• Own and refine the system's prompts, reasoning mechanisms, and context management to ensure seamless and accurate customer interactions.

• Identify and prioritize system needs within the product area, leading impactful projects that span multiple teams and drive significant improvements in customer support efficiency and satisfaction.

• Elevate the overall design maturity within the Support squad and deepen its understanding of context engineering principles and AI system design.

• Regularly engage with the broader Wise content and design community, particularly other Model and Content Designers, to evolve and share best practices for AI design.

• Champion the quality and effectiveness of AI-driven customer support solutions, setting clear benchmarks for success and ensuring they are met through delivered features.

📝 Enhancement Note: The responsibilities emphasize a blend of strategic leadership and hands-on design work, particularly in areas like prompt engineering, context engineering, and agentic design. The expectation is for the Principal AI Content Designer to not only design but also to influence and coach, indicating a significant impact on the team's capabilities and processes.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong academic foundation in a related field (e.g., Computer Science, Linguistics, Human-Computer Interaction, Design, Cognitive Science) would be beneficial. Emphasis is placed on practical, hands-on experience.

Experience: Extensive experience (implied 10+ years) in designing complex, large-scale automated systems, with a significant portion focused on AI-driven conversational interfaces. Proven experience in transitioning into or excelling within a Model Designer or systems-focused Content Designer role.

Required Skills:

• AI System Design: Proven expertise in designing complex, large-scale automated systems, specifically conversational AI experiences.

• Model Design / Systems Content Design: Demonstrated experience in architecting and implementing AI-driven user journeys.

• Prompt Engineering: In-depth understanding and practical application of common prompt engineering techniques and frameworks.

• Context Engineering: Strong grasp of how to manage and leverage context within AI systems for effective problem-solving.

• Agentic Design: Experience in defining and designing the behavior and interaction of AI agents.

• Cross-functional Collaboration: Ability to partner effectively with engineers, data scientists, and product managers in a fast-paced environment.

• Problem-Solving: Aptitude for tackling complex, ambiguous challenges and translating technical capabilities into user-centric solutions.

• Quality Focus: A keen eye for detail and a commitment to delivering high-quality, impactful user experiences.

• Influencing & Coaching: Capability to influence stakeholders, champion design principles, and coach teams on AI design methodologies.

• Empathy: High degree of empathy for both customers and colleagues.

Preferred Skills:

• Experience within the Fintech industry.

• Familiarity with specific AI/ML platforms or tools relevant to conversational AI development.

• Experience in scaling design processes and raising design maturity within product teams.

• Knowledge of knowledge architecture and guardrail design for AI systems.

📝 Enhancement Note: The "Heads up: this probably isn’t for you if..." section strongly implies that hands-on, deep technical expertise in AI systems, prompt engineering, context engineering, and agentic design is non-negotiable. Experience primarily in marketing, copywriting, or journalism without this technical AI focus is explicitly stated as unsuitable.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies of AI Systems: Detailed examples of designing and implementing large-scale automated or conversational AI systems, showcasing the problem, your design process, technical considerations, and outcomes.

• Prompt Engineering Examples: Demonstrations of sophisticated prompt design, including variations, context integration, and how prompts were iterated upon to achieve desired results.

• Context Engineering Demonstrations: Evidence of how context was architected and managed within an AI system to personalize or improve interactions.

• Agent Behavior Design: Examples illustrating how you defined the personality, decision-making logic, and interaction flows of AI agents.

• Metrics & Impact: Quantifiable results demonstrating the impact of your AI design work on customer experience, efficiency, or business objectives.

Process Documentation:

• Workflow Design & Optimization: Showcase how you've mapped, designed, and optimized complex user workflows within AI-driven systems.

• System Integration & Collaboration: Illustrate how your designs integrate with other technical components and how you collaborated with engineering and data science partners.

• Performance Analysis & Iteration: Provide examples of how you analyzed the performance of AI systems post-launch and iterated on designs based on data and user feedback.

📝 Enhancement Note: Given the "Principal" level and the explicit technical requirements, the portfolio is expected to be highly technical and results-oriented, focusing on the design and implementation of sophisticated AI systems rather than just UX or content strategy in a traditional sense.

💵 Compensation & Benefits

Salary Range: GBP £128,000 - £173,000 per year.

Benefits:

• Competitive Salary: A strong compensation package reflecting the seniority and specialized skills required for this role.

• Global Impact: Opportunity to contribute to a mission-driven company that is reshaping the financial industry for millions worldwide.

• Autonomy & Flexibility: High degree of freedom and flexibility in exploring and iterating on AI solutions.

• Learning & Development: Continuous learning opportunities as technology evolves, with support for professional growth.

• Inclusive Culture: Membership in a diverse, equitable, and inclusive international team that celebrates differences.

• Wise.Jobs Perks: Access to comprehensive benefits and information about working at Wise, detailed on their careers site.

Working Hours: 40 hours per week (standard full-time expectation).

📝 Enhancement Note: The salary range provided is substantial, reflecting the Principal level and the highly specialized nature of AI and conversational design expertise required. The benefits package, while not fully detailed, is implied to be competitive and aligned with a global tech company focused on employee well-being and professional development.

🎯 Team & Company Context

🏢 Company Culture

Industry: Global Technology / Fintech. Wise operates at the intersection of technology and finance, providing international money transfer and payment services. This context means the operations require high levels of security, compliance, and efficiency.

Company Size: Large (implied by global presence and number of employees, likely 1000+). This size suggests established processes but also opportunities for significant impact within specific product areas.

Founded: Wise was founded in 2011. This relatively young company history suggests a dynamic, innovative, and agile culture, likely less bureaucratic than older, more established institutions.

Team Structure:

• Content Design Guild: This role sits within the Content Design Guild, which is part of the broader Design team. This structure emphasizes a community of practice for shared learning and development in design disciplines.

• Squad Model: The role operates within a "squad," a cross-functional team likely comprising engineers, product managers, data scientists, and designers, focused on a specific product area (e.g., Wise Assistant for Support).

• Cross-functional Collaboration: The role necessitates deep collaboration with engineering, data science, and product management to co-architect AI systems and drive strategy.

Methodology:

• Agile Development: Given the tech and fintech nature, agile methodologies are highly probable for rapid iteration and development.

• Data-Driven Design: Decisions are expected to be informed by data science insights and customer usage metrics.

• Iterative AI Development: The role emphasizes rapid testing and iteration of AI ideas, acknowledging the evolving nature of AI technology.

• Systems Thinking: A focus on designing integrated systems rather than isolated features.

Company Website: https://wise.jobs/

📝 Enhancement Note: Wise's mission ("best way to move and manage the world's money") and slogan ("Min fees. Max ease. Full speed. For everyone, everywhere.") indicate a strong customer-centric ethos focused on efficiency, transparency, and accessibility. This likely translates into an operational culture that values pragmatism, speed, and user impact.

📈 Career & Growth Analysis

Operations Career Level: Principal. This signifies a senior individual contributor role with significant strategic influence, technical depth, and potential leadership responsibilities (e.g., mentoring, setting technical direction). The focus is on shaping core AI experiences and driving technical design maturity.

Reporting Structure: The role sits within the Content Design Guild, part of the Design team. The direct reporting line is likely to a Head of Design, Design Lead, or similar senior design management role. The day-to-day work involves close collaboration within a product squad.

Operations Impact: This role has a direct and significant impact on customer experience, operational efficiency (through automation), and the overall technological advancement of Wise's AI capabilities. By improving the Wise Assistant, the role contributes to reduced support costs, increased customer satisfaction, and a more seamless user journey across the Wise platform.

Growth Opportunities:

• Technical Specialization: Deepen expertise in advanced AI design, prompt engineering, and context engineering, potentially becoming a recognized authority in these fields within Wise.

• Leadership & Mentorship: Grow into a formal leadership role, managing design teams or spearheading AI design initiatives across the organization.

• Strategic Influence: Contribute to the long-term AI strategy and product roadmap for Wise, influencing how AI is leveraged across all offerings.

• Cross-functional Mastery: Develop a comprehensive understanding of product development, data science, and engineering within a leading fintech company.

• Community Building: Play a key role in evolving the practices and standards of the Content Design Guild and the broader AI design community at Wise.

📝 Enhancement Note: The "Principal" title implies that career growth may involve moving into management, becoming a lead architect, or taking on broader strategic responsibilities for AI product development at Wise. The emphasis on coaching and raising design maturity suggests opportunities to develop leadership and mentorship skills.

🌐 Work Environment

Office Type: On-site. The job listing specifies an on-site role at their London headquarters. This suggests a collaborative office environment designed to foster interaction and innovation.

Office Location(s): Worship Square, 65 Clifton Street, London, EC2A 4JE, United Kingdom. This is a central London location, implying a vibrant working environment with good access to transport links.

Workspace Context:

• Collaborative Design Hub: The office likely provides spaces conducive to collaborative work, brainstorming, and cross-functional team sessions, essential for AI system design.

• Access to Technology: As a tech company, expect access to modern hardware, software, and potentially specialized AI development tools and infrastructure.

• Team Interaction: Opportunities for regular, in-person interaction with engineers, data scientists, product managers, and fellow designers within the squad and the broader Design team.

• Company Culture Integration: Being on-site allows for full immersion in Wise's inclusive and dynamic company culture, fostering stronger team cohesion and alignment with company values.

Work Schedule: Standard 40-hour work week, with the expectation of on-site presence. While the role offers flexibility in exploring ideas, the core working hours and location are fixed.

📝 Enhancement Note: The on-site requirement suggests that Wise values in-person collaboration, spontaneous idea generation, and team building, which are often crucial for complex, rapidly evolving fields like AI design. The London headquarters is a hub for innovation and talent.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your application, CV, and portfolio to assess alignment with the core technical and experience requirements.

• Technical Interview / Design Challenge: Likely involves a deep dive into your experience with AI systems, prompt engineering, context engineering, and agentic design. This may include a practical design challenge or a detailed discussion of your portfolio case studies. Expect to articulate your technical thought process and problem-solving approach.

• Cross-functional Collaboration Discussion: Interviews with engineers, data scientists, and product managers to assess your ability to collaborate effectively, communicate complex ideas, and contribute to a shared vision.

• Hiring Manager / Senior Design Interview: Focus on strategic thinking, leadership potential, cultural fit, and alignment with Wise's mission and values. This stage will likely assess your ability to influence and coach.

• Final Round: Potentially a presentation of a portfolio case study to senior stakeholders or a panel, demonstrating your impact and strategic thinking.

Portfolio Review Tips:

• Technical Depth is Key: Prioritize showcasing your hands-on experience with AI systems, prompt engineering, context engineering, and agentic design. Clearly explain the technical challenges and your solutions.

• Quantify Impact: For each case study, clearly articulate the problem, your unique contribution, the metrics used to measure success, and the quantifiable outcomes (e.g., improved resolution rates, reduced customer effort, increased efficiency).

• Show, Don't Just Tell: Use diagrams, flowcharts, prompt examples, and system architecture visuals to illustrate your design process and technical solutions.

• Narrative of Complexity: Frame your case studies around complex problems that required sophisticated AI solutions. Explain your decision-making process, especially when navigating ambiguity or technical constraints.

• Highlight Collaboration: Demonstrate how you partnered with engineering and data science. Showcase examples of technical communication and shared problem-solving.

Challenge Preparation:

• AI System Design Scenario: Be prepared for a scenario where you need to design an AI assistant for a specific customer support need within Wise. Focus on agent behavior, prompt strategies, and context management.

• Prompt Engineering Exercise: You might be asked to refine existing prompts or design new ones for specific use cases, explaining your rationale.

• Technical Explanation: Practice articulating complex AI concepts (e.g., context windows, retrieval-augmented generation, agent loops) in a clear and concise manner to both technical and non-technical audiences.

• Strategy Articulation: Be ready to discuss your approach to defining the "automation strategy" for a squad and how you would champion design quality.

📝 Enhancement Note: The emphasis on technical expertise and the explicit exclusion of candidates without hands-on AI system experience means the interview process will heavily scrutinize practical skills and deep understanding of AI design principles.

🛠 Tools & Technology Stack

Primary Tools:

• AI/ML Platforms: Experience with platforms or frameworks used for building and deploying conversational AI models (specifics not mentioned, but likely involves working with internal or industry-standard tools).

• Design & Prototyping Tools: Standard design software (e.g., Figma, Sketch) for wireframing and prototyping AI interaction flows.

• Collaboration Tools: Tools like Slack, Jira, Confluence for team communication, project management, and documentation.

Analytics & Reporting:

• Data Analysis Platforms: Familiarity with tools used to analyze conversational data, user interaction metrics, and AI performance (e.g., Amplitude, Mixpanel, internal analytics dashboards).

• Performance Monitoring Tools: Tools for tracking AI model performance, error rates, and user satisfaction metrics.

CRM & Automation:

• CRM Systems: While not explicitly stated, understanding how AI assistants integrate with or augment CRM functionalities (e.g., Salesforce, Zendesk) is beneficial.

• Workflow Automation: Experience with designing or implementing automated workflows, potentially within the context of AI-driven customer service.

📝 Enhancement Note: The role requires deep technical acumen, implying familiarity with the underlying technologies that power AI systems, even if specific tool names aren't listed. The ability to work with data scientists and engineers means understanding their tools and workflows is crucial.

👥 Team Culture & Values

Operations Values:

• Customer Centricity: A core value is making customers' lives easier by providing fast, reliable, and affordable money transfer services, extended through intelligent AI assistance.

• Speed & Efficiency: "Min fees. Max ease. Full speed." This motto permeates the culture, driving a need for optimized processes and quick decision-making.

• Transparency & Fairness: Building trust through clear communication and equitable practices, applicable to both financial services and internal operations.

• Innovation & Agility: A willingness to embrace new technologies (like AI) and adapt quickly to market changes and evolving customer needs.

• Empowerment & Autonomy: Employees are expected to take ownership and drive initiatives, fostering a culture of responsibility and proactivity.

Collaboration Style:

• Cross-functional Partnership: Highly collaborative, with strong emphasis on seamless integration between design, engineering, data science, and product management.

• Guild-Based Learning: The Content Design Guild structure promotes knowledge sharing, peer feedback, and collective improvement of design practices.

• Direct Communication: A culture that likely favors direct and open communication to resolve issues quickly and efficiently.

• Data-Informed Discussions: Collaboration often involves leveraging data and insights to drive decisions and discussions.

📝 Enhancement Note: Wise's culture is characterized by its mission-driven approach, emphasis on speed and efficiency, and a commitment to inclusivity. The operations within this culture are expected to be fast-paced, collaborative, and focused on delivering tangible value to customers.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating Ambiguity: Working with rapidly evolving AI technology and defining new product paradigms presents inherent ambiguity. Candidates must be comfortable with this.

• Technical Complexity: Partnering effectively with highly technical teams (engineers, data scientists) requires a deep understanding of AI systems and the ability to communicate complex technical concepts.

• Scaling AI Impact: Designing AI systems that can effectively scale to serve millions of customers globally while maintaining quality and personalization is a significant challenge.

• Defining "Good": Establishing clear metrics and standards for AI performance and customer experience in a new domain requires strategic thinking and continuous refinement.

• Ethical AI Considerations: Ensuring responsible AI deployment, addressing bias, and maintaining user trust are ongoing challenges.

Learning & Development Opportunities:

• Cutting-Edge AI: Direct involvement in shaping the future of AI in financial services, with constant exposure to new research and techniques.

• Advanced Skill Development: Opportunities to master advanced prompt engineering, context engineering, agentic design, and AI system architecture.

• Mentorship and Influence: The Principal level offers a platform to mentor emerging talent and influence the strategic direction of AI design at Wise.

• Industry Exposure: Potential to represent Wise at AI conferences or contribute to industry best practices through the Content Design Guild.

• Career Pathing: Clear pathways for growth into senior technical leadership, AI product strategy, or management roles within Wise.

📝 Enhancement Note: The role presents significant challenges due to the cutting-edge nature of AI, but these challenges are directly tied to substantial growth and learning opportunities in a high-impact domain.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex AI system you designed. What were the core challenges, your design process, and the quantifiable impact?" (Focus on prompt engineering, context, agent behavior, and metrics).

• "How would you approach defining the automation strategy for a customer support AI assistant, considering potential risks and opportunities?" (Highlight your strategic thinking, quality focus, and understanding of Wise's mission).

• "Walk us through a time you had to collaborate with engineers and data scientists on a challenging technical project. What was your role, and how did you ensure alignment and success?" (Emphasize your technical communication and partnership skills).

• "How do you balance user needs with technical feasibility when designing AI experiences?" (Showcase your problem-solving and pragmatic approach). Company & Culture Questions:

• "What excites you about Wise's mission and its approach to money transfer?" (Connect your passion for AI design with Wise's customer-centric goals).

• "How would you contribute to raising design maturity within a team of engineers and data scientists?" (Demonstrate your coaching and influencing abilities).

• "Describe your experience working in an agile, fast-paced environment. How do you manage complexity and ambiguity?" (Highlight your adaptability and problem-solving skills).

• "How do you ensure inclusivity and fairness in AI systems you design?" (Address ethical considerations and empathy). Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly articulate the problem, your specific role and contributions, the design process (including technical details like prompt iteration, context management), the technical solutions implemented, and the measurable outcomes.

• Highlight Technical Ownership: Emphasize your deep involvement in the technical aspects of AI system design, not just the user interface.

• Quantify Everything: Use data and metrics to demonstrate the impact and ROI of your work.

• Be Prepared for Deep Dives: Expect detailed questions about your technical decisions, trade-offs, and the underlying AI principles.

• Showcase Collaboration: Explain how you worked with cross-functional teams, using specific examples.

📝 Enhancement Note: Interview preparation should heavily focus on demonstrating deep, hands-on technical expertise in AI systems design, prompt engineering, and context engineering. Case studies should be detailed, data-driven, and clearly illustrate your strategic impact and collaborative abilities.

📌 Application Steps

To apply for this AI Content Designer position:

• Submit your application through the provided link on SmartRecruiters.

• Curate Your Portfolio: Select 2-3 of your most impactful AI system design projects. For each, prepare a detailed case study focusing on prompt engineering, context engineering, agent behavior, technical collaboration, and quantifiable results. Ensure it clearly demonstrates your hands-on experience with large-scale automated systems.

• Tailor Your Resume: Highlight your experience with AI, conversational design, prompt engineering, context engineering, and agentic design. Use keywords from the job description and emphasize achievements related to designing complex automated systems and driving operational efficiency.

• Prepare for Technical Discussions: Brush up on AI concepts, prompt engineering techniques, and how to articulate complex technical solutions clearly. Practice explaining your portfolio case studies in detail, anticipating technical questions.

• Research Wise: Understand Wise's mission, products, and recent developments. Consider how AI can further enhance their customer experience and operational efficiency, and be ready to discuss your ideas.

⚠️ 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.