Backend Architect

Responsibilities:

Work with the 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, and 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, and auditing are 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, and 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 that the rest of the backend team learns from.

Requirements:

12+ years of software engineering experience, with significant time as a hands-on backend architect or senior backend engineer. This is a deeply hands-on role where you'll write the code, not just review it.

Production TypeScript experience in large, complex codebases you've shipped non-trivial backend systems in TS, ideally in a monorepo, and have strong opinions on how to structure a TS backend at scale.

Shipped a collaborative or real-time backend in production. WebSocket fanout, presence, document sync, and conflict resolution (CRDT, OT, or equivalent), you've owned this in a live multi-user product.

Strong database fundamentals. Schema design, indexing, query performance, transactions, migrations, consistency models. Comfortable making the call between relational, document, and event-sourced approaches based on the workload.

Multi-tenancy and auth depth: orgs, workspaces, RBAC, sharing semantics, and audit.

Comfortable with the Kubernetes and Terraform infra-surface and CI/CD, enough to debug, contribute, and design with infra-constraints in mind. You don't have to own it, but you can't be helpless around it.

Architect-level judgment without manager scope. You're the technical anchor, not a people manager.

Nice to Have:

Experience designing AI-aware backend APIs, streaming responses, long-running agent calls, token-bounded request/response shapes, idempotency for retried LLM ops, and cost attribution per tenant.

CRDT or OT internal experience with the Yjs, Automerge, or 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, and debugging production at scale.