Senior Software Engineer, Frontend - AI Platform

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and So Paulo. The Role We are currently seeking a Senior Frontend Software Engineer to join the AI Platform team , Addepars next-generation AI platform that enables seamless insights and interaction through natural language and data intelligence across our AI products. As a Senior Frontend Engineer , youll design and scale the interactive surface of AI Platform products. Youll work at the intersection of AI, design, and systems engineering, building a class of real-time AI experiences for users where every frame, token, and scroll behavior matters. You will collaborate closely with product design, backend, and AI/ML engineers to deliver smooth, trustworthy AI experiences that align with Addepars standards of performance, transparency, and reliability. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What Youll Do Design and implement complex, real-time UI features for conversational interfaces including chat streaming, incremental rendering, and dynamic layouts. Build high-performance WebSocket pipelines to handle streamed deltas, retries, and backpressure gracefully. Optimize scrolling and rendering performance using requestAnimationFrame, virtualization, intersection observers, and non-blocking state updates. Implement fault-tolerant UI logic for reconnection, cancellation, offline recovery, and retry without user disruption. Architect state management and caching strategies to maintain consistency between local UI and backend deltas. Collaborate with designers to deliver accessible, responsive, and pixel-perfect interfaces across themes and viewport sizes. Extend Addepars frontend developer experiencerefine the build pipeline (Vite/Webpack), test automation (Playwright, Jest), and linting/formatting standards (ESLint, Prettier). Instrument client-side telemetry and performance metrics to measure render latency, streaming lag, and user interaction speed. Mentor teammates through design reviews and pair programming, contributing to shared components and cross-product standards. Work closely with backend and AI/ML teams to co-design message formats, token streaming APIs, and session-level resiliency mechanisms. Shape the technical direction of AI Platforms frontend, contributing to shared libraries, caching strategies. Technical Fundamentals & Practices - Were looking for engineers who demonstrate mastery across the following practices and system fundamentals that empower to ship high-quality, low-latency conversational experiences at scale: Browser & Rendering Fundamentals : Deep understanding of the browsers rendering pipelineDOM, CSSOM, layout, paint, compositing. Ability to identify and fix layout thrashing, paint storms, and jank through Chrome DevTools performance profiling. Knowledge of animation scheduling via requestAnimationFrame, idle callbacks, and microtask queues.Familiarity with modern web APIs such as IntersectionObserver, ResizeObserver, MutationObserver, OffscreenCanvas, Web Workers, and BroadcastChannel for concurrent or cross-tab coordination. Asynchronous & Streaming Systems: Strong command of Promises, async/await, generators, and cancellation (AbortController). Familiarity with streaming data protocols (e.g., WebSockets, SSE) and patterns like batching, throttling, and debounce under load. Understanding of backpressure and how to pace UI rendering vs. message ingress. State & Data Synchronization: Experience designing immutable data flows with fine-grained updates (diffs, patches, deltas). Knowledge of caching, reconciliation, and hash-based change detection (e.g., djb2, CRC32, content hashing). Practices for ensuring consistency between transient client state and authoritative backend models. UI Architecture & Composition: Familiarity with reactive component frameworks (Svelte preferred; React/Vue acceptable). Experience isolating side effects, using stores/signals, and maintaining predictable reactivity graphs. Ability to decompose large applications into feature modules with lazy loading, error boundaries, and shared design tokens. Ability to evaluate and Who We