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We are on a mission to reinvent how designers work in the AI era. We’re backed by top investors including First Round, Chemistry, Homebrew, Scribble and senior leaders from OpenAI, Meta, Google, Ramp, Stripe and more. We’re building the next-generation AI design tool for product teams.
We’re hiring a Backend Architect to own the backend that powers a collaborative, real-time canvas used by design teams. You’ll architect the API surface, data layer, and real-time sync that everything else in the product builds on — including every AI feature. This is a deeply hands-on architect role: you’ll design the system and write the code, not just draw boxes.
Our backend is TypeScript end-to-end, multi-tenant, and serves a live multi-user canvas. You’ll set the patterns the rest of the team builds against.
Work with AI Lead, and own parts of the backend architecture. API design, data modeling, service boundaries, real-time sync, auth and multi-tenancy. Make the calls that everyone else’s code lives inside
Build the real-time and multiplayer layer. WebSocket fanout, presence, conflict resolution, document sync — the substrate that makes the canvas feel live for every user in a workspace
Design the data layer with judgment, not defaults. Pick the right store for each workload — relational, document, event log, blob, cache — and own the schemas, migrations, and consistency model
Ship into our TypeScript monorepo. API, auth, database, and real-time services all live in one codebase — you’ll work across all of them and set the patterns for how they fit together
Own auth, orgs, and permissions. Workspaces, sharing, roles, audit — the things that make us safe to use inside a company
Build AI-friendly backend primitives. Streaming endpoints, long-running agent calls, idempotency, cost attribution — the AI features will call into your APIs and you’ll make sure they can
Set the technical bar for backend engineers. Code review, design review, and the patterns the rest of the backend team learns from
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Experience designing AI-aware backend APIs — streaming responses, long-running agent calls, token-bounded request/response shapes, idempotency for retried LLM ops, cost attribution per tenant
CRDT or OT internals experience — Yjs, Automerge, ShareJS lineage, or having built your own
Background shipping canvas, design-tool, IDE, or collaborative-document backends
Experience with observability and reliability engineering at a serious level — SLOs, on-call, debugging production at scale
The backend architecture and the patterns it enforces
The real-time / multiplayer layer the canvas depends on
The data layer — schemas, stores, migrations, consistency
Auth, multi-tenancy, and permissions
The backend primitives every AI feature calls into
The technical bar for backend code in the monorepo
Verified company details for this employer are not available yet.
Full-time
Senior · 12+ years experience
Onsite
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