Senior AI Product Engineer (React / Typescript) - UX

📍 Job Overview

Job Title: Senior AI Product Engineer (React / Typescript) - UX

Company: Landytech

Location: London, England, United Kingdom

Job Type: Full-Time

Category: Product Engineering / UX / Operations (GTM Enablement)

Date Posted: 2026-09-21

Experience Level: 5-10 Years

Remote Status: Hybrid

🚀 Role Summary

• This role focuses on owning the end-to-end product experience for Landytech's Sesame platform, emphasizing the seamless integration of AI in both design and engineering workflows.

• You will be instrumental in building and maintaining a code-based design system, ensuring consistency and high standards across all interfaces, particularly for data-dense financial applications.

• The position requires a strong blend of front-end engineering expertise (React, TypeScript) and deep UX judgment to direct AI-assisted development effectively, ensuring it meets product logic, density, and intent.

• You will collaborate closely with users, product managers, and engineers to translate user feedback into tangible product improvements and define the standards for AI-driven interface generation.

📝 Enhancement Note: While the title is Senior AI Product Engineer, the core responsibilities and emphasis on UX, design systems, and client journey ownership align strongly with a Product Operations or GTM Enablement focus, particularly in a tech-forward company leveraging AI for product development. The role bridges engineering, product, and user experience to ensure the platform is not only functional but also intuitive and effective for financial professionals.

📈 Primary Responsibilities

• End-to-End Product Experience Ownership: Lead the definition and implementation of the client journey, interaction logic, and overall look and feel of the Sesame platform, ensuring a cohesive and intuitive user experience.

• Design System Development & Maintenance: Contribute significantly to the design system, which is developed in code, serving as a central repository for UI components and patterns used by both engineers and AI tooling.

• AI-Assisted Development Direction: Define and enforce the standards, instructions, and rules that guide AI tools in generating interfaces, critically assessing output for accuracy, consistency, and adherence to product intent.

• Data-Dense Interface Crafting: Build and optimize complex financial interfaces, including virtualised tables and charting, ensuring legibility, precision, and performance under real-world data loads.

• User-Centric Design & Feedback Integration: Engage directly with investment professionals, family offices, and advisors to gather insights, validate design decisions, and iterate on the product experience based on user needs.

• Consistency and Quality Assurance: Uphold and define the product's look, feel, and consistency across all features, acting as an editor and enabler by reviewing work, teaching best practices, and holding a high standard.

• Cross-Functional Collaboration: Work closely with product managers and engineers to integrate AI into all stages of the product lifecycle, from design conceptualization to engineering implementation.

• Tooling and Process Evolution: Actively participate in evolving the tooling and processes that support AI-assisted design and development, contributing to innovation and efficiency improvements.

📝 Enhancement Note: The responsibilities highlight a critical role in bridging the gap between AI capabilities and sophisticated user experience in a complex financial domain. This involves not just building but also strategizing and standardizing how AI is leveraged for product development, which is a key aspect of modern Product Operations and GTM enablement for tech products.

🎓 Skills & Qualifications

Education:

• While no specific degree is mandated, a Bachelor's degree in Computer Science, Engineering, Design, or a related field is often preferred for roles of this seniority and technical depth.

• A strong portfolio demonstrating practical application of skills is more valued than formal education alone. Experience:

• 5+ years of hands-on experience in front-end engineering.

• Proven track record of building and maintaining production-level design systems.

• Experience developing and managing complex, data-dense interfaces, including virtualised tables and charting solutions.

• Demonstrated ability to work directly with end-users and incorporate their feedback into product development cycles. Required Skills:

• React & TypeScript Proficiency: Deep expertise in building modern web applications using React and TypeScript.

• Design System Development: Proven experience in creating, maintaining, and scaling design systems in code, with familiarity with libraries like shadcn/ui.

• Data-Dense Interface Expertise: Skilled in handling and presenting large volumes of data effectively, including virtualised tables, real-time charting, and performance optimization for complex financial data.

• UX Judgment & Design Thinking: Strong ability to critique user flows, think in terms of objects, relationships, and states, and apply principles of hierarchy, typography, density, and restraint.

• AI-Assisted Development Fluency: Comfort and experience with AI-assisted development tools, with a focus on specifying standards and critically evaluating AI output.

• User Interaction & Feedback Integration: Experience in directly engaging with clients/users, understanding their needs, and translating that into product requirements and improvements.

• Editing & Enabling Capabilities: Ability to review others' work, provide constructive feedback, teach best practices, and maintain a consistent product vision.

Preferred Skills:

• Product Management Instincts: Experience in client-facing roles, making product decisions, and owning outcomes beyond specific tickets.

• Financial Domain Curiosity: A genuine interest in understanding financial concepts, investment reporting, and the asset management industry.

• Cross-functional Leadership: Experience leading initiatives, mentoring junior engineers, and influencing product strategy.

• Knowledge of Observability Tools: Familiarity with tools that help monitor application performance and user behavior in production.

📝 Enhancement Note: The emphasis on "directing AI to our standard, consistently and at depth" and "engineering work: it lives in the repo, in the tooling, and in what the agents can and cannot reach for" strongly suggests a need for candidates who understand the operationalization of AI in a product development context. This implies an understanding of how to set up, manage, and refine AI workflows for consistent, high-quality output, a core function within advanced Product Operations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Shipped Interfaces: Showcase a collection of interfaces you have built and shipped, with a focus on complex, data-dense applications relevant to financial services or similar domains.

• Design System Contributions: Evidence of your involvement in building or significantly contributing to a production design system, demonstrating your understanding of component-based architecture and maintainability.

• AI-Assisted Development Examples: If possible, provide examples or case studies illustrating how you have used AI tools in your development process, particularly focusing on how you directed or refined AI output to meet specific product standards.

• Process Improvement Case Studies: Prepare detailed case studies that highlight a specific problem you identified in a user flow or interface, the steps you took to improve it (potentially involving AI or design system enhancements), and the measurable impact of your changes.

Process Documentation:

• Workflow Design & Optimization: Be prepared to discuss how you approach designing and optimizing user workflows, especially in complex financial contexts where precision and clarity are paramount.

• System Implementation & Standards: Articulate your experience in implementing design systems and setting standards for both human engineers and AI agents to follow, ensuring consistency and scalability.

• Measurement & Performance Analysis: Demonstrate your ability to define key metrics for interface performance, user engagement, and design system adoption, and how you use data to inform further iterations and improvements.

📝 Enhancement Note: The explicit mention of "No portfolio required. Shipped interfaces we can look at, and the decisions behind them, is what we want to see" and the emphasis on "directing AI to our standard, consistently and at depth" means the portfolio should not just showcase what was built, but how and why, with a strong focus on the strategic direction and operationalization of design and development processes, especially concerning AI.

💵 Compensation & Benefits

Salary Range:

• For a Senior AI Product Engineer with 5-10 years of experience in London, UK, the estimated salary range is typically between £75,000 and £110,000 per annum. This range can vary based on the candidate's specific experience, the depth of their UX judgment, and their proficiency with AI-assisted development.

• Methodology: This estimate is derived from current market data for senior front-end engineering roles in London, factoring in the specialized skills in AI-assisted development, design systems, and UX, which command a premium. Data sources include industry salary benchmarks, recruitment agency reports for tech roles in London, and general cost of living considerations for the region.

Benefits:

• Competitive Salary & Stock Options: Offers financial reward and ownership in the company's success.

• Hybrid Working: Provides flexibility to balance office collaboration with remote work.

• Private Medical Insurance: Comprehensive coverage with Bupa for the employee and their family, ensuring access to healthcare.

• Death in Service Insurance Option: A valuable benefit providing financial security for dependents.

• Pension Plan: Contribution to a NEST pension plan to support long-term financial planning.

• Cycle to Work Scheme: Encourages sustainable commuting and offers tax savings on bicycle purchases.

• Gym Allowance: Supports employee well-being and fitness.

• Office Food & Drinks, Regular Socials: Enhances the office experience and fosters team camaraderie.

Working Hours:

• The role is based on a standard full-time employment contract, likely equating to approximately 40 hours per week.

• The hybrid working model suggests flexibility in structuring these hours, with an expectation of core collaboration days in the London office.

📝 Enhancement Note: The salary range is an estimate based on market data for comparable roles in London. Actual compensation will be determined by the company based on the candidate's qualifications, experience, and negotiation. The benefits package is comprehensive and typical for a growing tech company in the UK.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Technology (FinTech), specifically focusing on investment reporting and asset information access. Landytech operates in a market driven by data accuracy, client trust, and technological innovation.

Company Size: 80+ staff, indicating a growing mid-stage company that has moved beyond startup phase but still retains agility and a strong growth trajectory. This size often means operations are becoming more formalized, but individual impact is still significant.

Founded: 4 years ago, with significant Series B funding secured in January 2023. This signifies rapid growth, market validation, and investment in scaling operations and product development.

Team Structure:

• Operations Team Aspect 1: The Product Engineering and UX team is likely structured to be agile and cross-functional, working closely with product management and AI specialists. The team size is not specified but is implied to be growing.

• Operations Team Aspect 2: Reporting structure is likely to involve a Head of Product, VP of Engineering, or similar leadership, with this Senior role having significant autonomy and influence within its domain.

• Operations Team Aspect 3: High emphasis on cross-functional collaboration, particularly with Product Management, AI teams, and directly with end-users, to ensure product-market fit and exceptional user experience.

Methodology:

• Operations Process 1: Data-driven decision-making is core, with AI heavily integrated into design and engineering. This implies a focus on metrics, performance analysis, and iterative improvement based on user data and AI output analysis.

• Operations Process 2: Agile and iterative workflow planning, with a strong emphasis on evolving tooling and processes. The design system being code-based is a key part of this methodology, enabling rapid iteration and consistent application.

• Operations Process 3: Automation and efficiency are paramount, with AI not just as a feature but as a core part of the development process. This role is about directing and optimizing this automation for product coherence and quality.

Company Website: https://landytech.com/

📝 Enhancement Note: Landytech's rapid growth and significant funding suggest an environment that values innovation, speed, and a strong product vision. The company's diverse international team hints at an inclusive culture that benefits from varied perspectives, crucial for developing a global product.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a "Senior" individual contributor, implying a high level of technical expertise, autonomy, and the ability to influence product direction and team practices. It's a role for someone who can not only execute but also strategize and lead by example, particularly in the nascent field of AI-assisted product development.

Reporting Structure: The role will likely report into a Head of Product, VP of Engineering, or a similar senior product leader. There's an expectation of significant direct interaction with product managers and other engineers, fostering a collaborative and flat hierarchy.

Operations Impact: The Senior AI Product Engineer will have a direct and substantial impact on the user experience and perceived quality of the Sesame platform. By owning the front-end experience layer and setting standards for AI, they will directly influence client satisfaction, adoption rates, and the overall competitiveness of Landytech's offering in the FinTech market. Their work will be critical in ensuring the platform delivers on its promise of faster, more informed investment decisions.

Growth Opportunities:

• Operations Skill Advancement: Deepen expertise in AI-assisted development, potentially leading to specialized roles in AI product strategy or tooling development. Opportunity to become a subject matter expert in this cutting-edge area.

• Design System Leadership: Grow into a lead role for the design system, influencing its architecture, adoption across teams, and evolution.

• Product Strategy Influence: With direct client interaction and ownership of the user journey, there's potential to move towards more strategic product management or product ownership roles, guiding the roadmap based on user needs and technological possibilities.

• Mentorship & Team Development: As a senior member, opportunities to mentor junior engineers and designers, contributing to the growth of the broader product team.

• Industry Specialization: Develop deep expertise in the FinTech sector and the specific challenges of financial data visualization and reporting.

📝 Enhancement Note: The role offers a unique opportunity to shape the future of product development by integrating AI, making it highly attractive for ambitious engineers looking to be at the forefront of technological innovation in a growing company.

🌐 Work Environment

Office Type: Landytech offers a Hybrid working model, balancing the benefits of in-office collaboration with remote flexibility. This suggests a modern office setup designed to facilitate teamwork, brainstorming, and focused work.

Office Location(s): The primary office is located in London, England, United Kingdom. This central location offers access to a vibrant tech ecosystem and talent pool.

Workspace Context:

• Collaborative Environment: The office is designed to foster interaction, likely featuring open-plan areas, meeting rooms, and breakout spaces conducive to teamwork and cross-pollination of ideas between engineering, product, and UX.

• Operations Tools & Technology: Employees will have access to modern development tools, robust infrastructure, and the latest AI-assisted development platforms. The company's commitment to evolving tooling means this environment is dynamic and forward-thinking.

• Team Interaction: The hybrid model encourages intentional in-office days for team syncs, design reviews, and collaborative problem-solving sessions, ensuring strong team cohesion despite distributed work.

Work Schedule:

• The hybrid model implies a degree of flexibility in daily working hours, while adhering to a standard full-time commitment (approx. 40 hours/week). Core hours are likely expected for team meetings and collaborative sessions, with flexibility around start and end times.

📝 Enhancement Note: The hybrid setup in a major tech hub like London is designed to attract and retain talent by offering a balance of flexibility and collaborative synergy, which is essential for product development roles that require both individual focus and team input.

📄 Application & Portfolio Review Process

Interview Process:

• Portfolio/Work Conversation: An initial discussion focused on reviewing your shipped interfaces and the decisions behind them. Be prepared to articulate your design philosophy, technical choices, and the impact of your work, especially concerning data-dense interfaces and design systems.

• Short Practical Exercise: A focused, hands-on task based on a real Sesame flow. This will likely assess your ability to apply your UX judgment and technical skills to a specific problem, potentially involving AI tool usage or design system application.

• Working Session: A collaborative session with a product manager and an engineer. This will evaluate your ability to work within a team, communicate your thought process, and contribute to problem-solving in a live environment. Expect discussions around product strategy, user needs, and technical feasibility.

• Final Evaluation: Assessment of your overall fit, problem-solving capabilities, and potential to contribute to Landytech's mission.

Portfolio Review Tips:

• Focus on Impact & Rationale: Don't just show screenshots; explain the problem, your solution, the tools and processes you used (including AI if applicable), and the measurable outcomes. For this role, emphasize how you ensured consistency and directed AI output.

• Showcase Design System Experience: Detail your contributions to design systems, highlighting how you managed components, enforced standards, and facilitated adoption.

• Highlight Data-Dense Interface Skills: Present examples of complex tables, charts, or dashboards, explaining your approach to performance, clarity, and user interaction.

• Demonstrate UX Judgment: Be ready to critique existing flows and articulate why certain design choices are superior, particularly in the context of financial data and AI-generated interfaces. Explain how you "read the output critically enough to see why something is subtly wrong."

Challenge Preparation:

• Understand the "Must-Have": Re-read the job description's emphasis on "setting the standard AI works to." Prepare to discuss how you would define and enforce these standards for AI-generated interfaces in a financial context.

• Practice Articulating UX Decisions: Be ready to explain your design rationale clearly and concisely, especially when discussing complex data and interaction logic.

• Research Landytech and Sesame: Understand their mission, the product's purpose, and the target audience (investment managers, advisors). Consider the specific challenges of presenting dense financial data effectively.

📝 Enhancement Note: The interview process is designed to be practical and collaborative, emphasizing real-world application of skills and the ability to work with both users and AI. A strong portfolio that demonstrates strategic thinking behind interface design and development, especially concerning AI integration, will be key.

🛠 Tools & Technology Stack

Primary Tools:

• React: The core JavaScript library for building user interfaces. Expertise in React is essential.

• TypeScript: A superset of JavaScript that adds static typing, crucial for large-scale application development and maintainability.

• Shadcn/ui: A popular component library built on Radix UI and Tailwind CSS, offering accessible and customizable UI elements. Experience with this or similar component libraries is highly valued.

• AI-Assisted Development Tools: Proficiency with current AI tools used in design and engineering, and the ability to integrate them effectively into workflows. This is a key differentiator.

Analytics & Reporting:

• Data Visualization Libraries: Experience with charting libraries (e.g., Chart.js, D3.js, Recharts) for creating interactive and informative financial data visualizations.

• Performance Monitoring Tools: Familiarity with tools to track front-end performance, especially for data-intensive applications (e.g., Lighthouse, Web Vitals).

• User Behavior Analytics: Tools to understand how users interact with the interface, which can inform design iterations.

CRM & Automation:

• While not explicitly mentioned for this role, understanding how front-end applications integrate with back-end systems, APIs, and potentially CRM data is beneficial.

• Workflow Automation: Experience in automating repetitive tasks in the development lifecycle, which may extend to how AI tools are automated or triggered.

📝 Enhancement Note: The technology stack emphasizes modern front-end development practices with a significant emphasis on AI integration. Candidates should be comfortable with cutting-edge tools and understand how to leverage them for efficiency and quality in product development.

👥 Team Culture & Values

Operations Values:

• Product Coherence & Intent: A strong belief that the product should feel like a unified entity, with every element expressing its underlying logic and intent, not just reusing components. This drives a focus on detail and consistency.

• Data-Driven Iteration: Decisions are informed by user feedback, performance metrics, and critical analysis of AI output. There's a commitment to continuous improvement based on empirical evidence.

• Craftsmanship & Quality: A dedication to building high-quality, robust, and aesthetically pleasing interfaces, particularly for complex financial data where precision is critical.

• AI as a Lever: Viewing AI not just as a tool but as a fundamental part of the product development process, requiring intelligent direction and rigorous oversight to achieve desired outcomes.

• User-Centricity: A core value of understanding and serving the needs of investment professionals and their advisors, ensuring the product delivers real value.

Collaboration Style:

• Collaborative Editing & Enabling: A culture where team members actively review each other's work, provide constructive feedback, and share knowledge to uplift the entire team's capabilities.

• Cross-Functional Integration: Seamless collaboration between engineering, product management, and UX, with a shared responsibility for the product's success.

• Openness to Evolving Processes: A willingness to experiment with new tools and methodologies, understanding that the landscape of AI-assisted development is rapidly changing.

• Direct User Engagement: A proactive approach to involving end-users in the development process, fostering a feedback loop that drives product relevance and user satisfaction.

📝 Enhancement Note: The culture at Landytech appears to be driven by innovation, a commitment to quality, and a user-focused approach, amplified by the strategic integration of AI. The emphasis on collaboration and continuous learning is key for a role at the cutting edge of product development.

⚡ Challenges & Growth Opportunities

Challenges:

• Directing AI Consistently: The primary challenge is moving beyond simply using AI to directing it effectively and consistently to produce interfaces that meet nuanced product logic and high standards, especially in a dense financial domain.

• Balancing AI Output with UX Judgment: Ensuring that AI-generated interfaces are not just aesthetically pleasing or component-compliant but also strategically sound from a user experience perspective, requiring constant critical evaluation.

• Evolving Tooling & Methodologies: The rapid pace of AI development means tools and best practices are constantly changing, requiring continuous learning and adaptation.

• Translating Complex Financial Data: Crafting interfaces that make dense, complex financial information comprehensible and actionable for sophisticated users.

• Upholding Design System Integrity: Maintaining the coherence and integrity of the design system as it is used and influenced by both human engineers and AI agents.

Learning & Development Opportunities:

• AI Product Development Specialization: Become a leader in AI-driven product engineering and UX, a highly sought-after skill set.

• Advanced Front-End Techniques: Deepen expertise in areas like virtualised tables, performance optimization for large datasets, and modern React/TypeScript patterns.

• FinTech Domain Expertise: Develop a strong understanding of investment reporting, asset management, and the financial advisory landscape.

• Product Strategy & User Research: Gain hands-on experience in direct user engagement, product roadmap input, and strategic decision-making.

• Mentorship and Leadership: Opportunities to mentor junior team members and potentially lead initiatives within the product engineering domain.

📝 Enhancement Note: This role presents a significant opportunity to tackle complex, forward-thinking challenges at the intersection of AI, UX, and FinTech, offering substantial growth potential for ambitious professionals.

💡 Interview Preparation

Strategy Questions:

• AI Direction & Standards: "How would you establish and enforce standards for AI-generated interfaces to ensure they consistently reflect product logic, density, and intent, particularly for complex financial data?" (Prepare examples of how you'd define prompts, review criteria, and feedback loops.)

• UX Judgment vs. AI Output: "Describe a situation where an AI-generated design conflicted with good UX principles. How did you identify the conflict, and what steps did you take to resolve it?" (Focus on your critical evaluation skills and ability to articulate UX rationale.)

• Design System Evolution: "Imagine you're tasked with expanding our code-based design system to accommodate new AI-generated components. What process would you follow to ensure consistency and maintainability?" (Discuss your approach to component architecture, documentation, and integration.)

Company & Culture Questions:

• Landytech's AI Strategy: "Based on your understanding of Landytech, how do you see AI further transforming the investment reporting landscape, and what role would this position play in that transformation?" (Research Landytech's mission and AI integration.)

• Team Collaboration: "This role requires collaboration with engineers, product managers, and direct user interaction. How do you approach building relationships and ensuring effective communication across these different groups?" (Provide examples of your collaborative working style.)

• Impact Measurement: "How would you measure the success of your contributions to the Sesame platform's user experience, particularly in relation to AI-assisted development and design system adoption?" (Think about metrics related to user satisfaction, efficiency, and consistency.)

Portfolio Presentation Strategy:

• Storytelling for Impact: Structure your portfolio walkthroughs around specific projects, narrating the problem, your strategic approach (including AI use), the execution, and the measurable results.

• Highlighting AI Direction: For any relevant projects, clearly articulate your role in directing or refining AI output, showcasing your critical assessment and ability to enforce standards.

• Demonstrating UX Judgment: Be prepared to deeply explain the "why" behind your design decisions, especially concerning hierarchy, density, and interaction logic in complex interfaces.

• Conciseness and Clarity: Given the technical nature, ensure your explanations are clear, concise, and tailored to your audience, avoiding overly technical jargon where simpler terms suffice.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong understanding of Landytech's unique approach to AI-driven product development, showcasing both technical proficiency and strategic UX thinking. Your ability to articulate how you would direct AI and maintain product consistency will be paramount.

📌 Application Steps

To apply for this Senior AI Product Engineer position:

• Submit your application through the provided link on Workable.

• Portfolio Customization: Tailor your resume and, if submitting one, your portfolio to highlight your experience with React, TypeScript, design systems, and particularly your ability to direct AI-assisted development. Showcase examples of complex, data-dense interfaces you've built.

• Resume Optimization: Ensure your resume clearly articulates your 5+ years of front-end experience, your contributions to design systems, and any experience working with AI tools in a product development context. Quantify achievements where possible.

• Interview Preparation: Thoroughly review the job description and company information. Prepare specific examples and case studies that demonstrate your UX judgment, your approach to setting and enforcing standards for AI, and your ability to collaborate effectively. Practice articulating your thought process for the practical exercise.

• Company Research: Deeply understand Landytech's mission, its product (Sesame), its market position in FinTech, and its innovative approach to integrating AI. Research their recent funding rounds and company growth to understand the environment you'd be joining.

⚠️ 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.