As the Lead Software Engineer for our Frontend Platform team, your mission is to build a production-ready frontend ecosystem engineered from the ground up for autonomous and AI-assisted software development. This is a greenfield role where you will scale our early-stage architecture into a robust production environment and establish our core design system from scratch. Instead of building a traditional developer platform solely for human engineers, you will design a highly deterministic repository structure, runtime abstractions, and strict architectural guardrails. Your primary goal is to ensure that AI agents have the high-fidelity context, type safety, and safety nets they need to safely ship high-performance UI features for our 5+ product engineering teams. You will head our Frontend Center of Excellence, redefining what it means to build software when AI is the primary author.
What you’ll do
- Lead the Center of Excellence: guide both the frontend community and the wider engineering org as we shift to AI-native software development. You'll set standards that make this feel natural: prompt engineering practices, clear repository boundaries, and automated code mods that keep quality high as development accelerates.
- Harden the Autonomous Platform Foundation: take our early-stage frontend architecture to production, establishing a highly performant monorepo structure, efficient local development setups, and automated CI/CD pipelines optimized for rapid development loops.
- Co-create the Design System: partner directly with Product Design to launch a token-driven, highly composable component library from scratch, establishing automated design-to-code synchronization and deterministic component behaviors that make UI assembly foolproof for AI agents.
- Enable Product Team Autonomy: design a self-service platform infrastructure, including instant preview environments, and isolated local development workspaces, that allows feature teams to independently test and deploy their workloads end-to-end.
- Engineer the LLM Context Layer: design and maintain the repository's semantic context layer, including structured markdown rules, machine-readable architectural manifests, and tight end-to-end TypeScript types, ensuring AI coding tools possess perfect context of system boundaries.
What we’re looking for
- Engineering Leadership: you know how to bring people along, not just set direction. You’re comfortable influencing without authority and building trust across product, design, and engineering teams.
- Scaling Frontend Platforms: proven track record of scaling a shared frontend platform across multiple distributed engineering teams. You understand the full lifecycle of platform ownership, including managing shared package dependencies, controlling bundle-size bloat, handling zero‑downtime framework upgrades, and measuring developer friction to clear delivery bottlenecks.
- Decentralized Platform Philosophy: a clear architectural preference for building self‑service, decoupled developer tools (such as isolated preview environments and custom CLIs) that eliminate centralized engineering bottlenecks.
- Component‑Driven API Design: deep experience engineering reusable UI primitives with strict separation of concerns (such as headless UI or design‑token‑driven architectures), utilizing explicit, typed contracts rather than fragile, highly mutable component configurations.
- Modern Tooling Fluency: deep technical expertise in TypeScript and contemporary frontend web architectures (e.g. Vite, Turborepo, Nx, and package‑manager workspaces) with a strong focus on maximizing local development speed.