We build API-first back-ends and integration layers in Node.js with GraphQL and REST.
Node.js runs our APIs, integration layers and background jobs. One language across front and back end reduces context-switching and makes shared validation logic practical.
The engine behind the interface
Node.js runs our APIs, integration layers and background processing. Its concurrency model suits the work we do most — systems that spend their time waiting on databases, third-party APIs and webhooks rather than performing heavy computation. That is the shape of nearly every integration and commerce workload.
Sharing one language across the front and back end has a practical benefit beyond convenience: validation rules, type definitions and business logic can be genuinely shared rather than reimplemented twice and allowed to drift apart.
How we structure it
API-first, with the contract documented before implementation, so your mobile app, partner integration and reporting layer all consume the same interface. GraphQL where clients need flexible, precise queries; REST where simplicity and cacheability matter more. Background jobs and queues for anything slow, so a user-facing request never waits on a third party.
Integration code is built for failure rather than the happy path: retries with backoff, idempotency so a repeated webhook cannot duplicate an order, dead-letter queues that surface problems to a human, and structured logging that makes a two-week-old incident reconstructable.
Operational reality
Everything is containerised and deployed through the same pipeline as the rest of the stack, with health checks, metrics and alerting configured before launch. Dependency and vulnerability scanning runs continuously, because the Node ecosystem's greatest strength — an enormous library of packages — is also its main supply-chain risk, and treating that seriously is not optional in production.
Why Node for the back end?
Shared language across the stack reduces context-switching and duplicated logic, and the ecosystem for API and integration work is deep. For I/O-heavy workloads — which most integration work is — it performs well and staffs easily.
How do you handle long-running or heavy jobs?
Off the request path. Queues, workers and scheduled processes with retry and dead-letter handling, so a slow third-party system degrades one job rather than the whole application.
Is it suitable for regulated workloads?
Yes, with the surrounding discipline: dependency scanning, pinned versions, secrets management, structured logging and least-privilege access. The language matters less than the controls around it.