Job Description

Role purpose

As the Principal UI Architect at Prevalent AI, you will own and drive the end-to-end front-end architecture vision for our Data Fabric and Exposure Management platforms. You will define the future-ready UI ecosystem that powers intelligent, agentic user experiences, self-serve analytics, advanced visualizations, and high-performance, scalable applications.



This role goes beyond building UIs--it is about designing a modern, resilient, AI-augmented architecture that supports rapid development, exceptional quality, and long-term product evolution. You will identify structural gaps, elevate engineering standards, and establish the patterns, processes, and guardrails needed for world-class UI development.



You will collaborate deeply with UX, product, backend, platform, and AI engineering teams to translate complex requirements into elegant, performant frontend systems. As the technical leader for UI across the organization, you will mentor engineers, drive architectural coherence, elevate code quality, and influence strategic product direction.



If you are passionate about crafting sophisticated UI systems, solving large-scale architectural challenges, and shaping the future of AI-driven, exploratory, and analytical interfaces--this is your opportunity to create lasting impact.

Key accountabilities

Strategic Architecture Leadership

Define the long-term UI architecture aligned with product strategy, including agentic experiences for Data Fabric and Exposure Management. Architect a future-ready front-end platform that supports: agent-driven workflows self-serve dashboarding and reporting graph-based and advanced analytical visualisations real-time, data-intensive applications Lead the evolution from traditional dashboards toward intelligent, adaptive, AI-augmented UI systems.

Quality, Reliability & Structural Excellence

Champion engineering excellence by identifying root causes of quality issues across: technical design component structure code organization state management testing strategy development processes and toolchains Establish architecture guidelines, coding standards, and review practices that raise product robustness and maintainability. Drive adoption of scalable component frameworks, reusable UI libraries, and consistent design patterns.

AI-Driven Developer Velocity

Introduce and operationalize AI tools to improve developer velocity (code generation, refactoring, test creation, documentation, automation). Define workflows where AI assists in rapid prototyping, design-to-code translation, visualisation generation, and repetitive development tasks. Build pipelines and guardrails ensuring AI-assisted code meets security, quality, and performance standards.

Hands-On Technical Leadership

Architect and guide the development of complex UI components for web-scale systems. Build reusable, performance-optimized libraries and frameworks for dashboards, graphs, and data-intensive interfaces. Lead the design of high-performance frontend systems with efficient rendering, minimal re-renders, and scalable state management. Bridge frontend and backend concerns to ensure cohesive, maintainable, future-proof systems.

Advanced Visualisation & Interaction Capabilities

Lead the architecture for data visualisations including graphs, networks, hierarchical layouts, and interactive analytical interfaces. Ensure visualisation performance for large-scale, streaming, and real-time datasets.

Cross-Functional Leadership & Collaboration

Work closely with UX, product, platform engineering, and AI teams to translate conceptual designs and exploration workflows into scalable UI systems. Conduct architectural reviews, mentor UI/UX engineers, and drive continuous improvement across the team. Ensure alignment between frontend, backend, and data pipelines for seamless user experiences.

Skills and Experience

Proven expertise in designing large-scale, high-performance UI architectures for enterprise products. Extensive experience with React, GraphQL , TypeScript, and modern JS micro-frontend patterns. Strong background in architecting visualization systems for complex datasets, including graph-based UIs. Deep understanding of rendering lifecycle, performance tuning, and browser-level optimisations . Strong ability to analyze codebases and processes to identify architectural and structural gaps affecting quality. Experience in designing AI-assisted development workflows and improving developer velocity using AI tools. Ability to build reusable component frameworks, design systems, and UI libraries. Excellent collaboration, leadership, and problem-solving skills. Comfortable working in high- pace environments and proficient in Agile methodologies. * Demonstrated ability to mentor engineering teams and influence technical direction across the organisation .