A backend development company builds and maintains the server side of a product: the APIs that web and mobile clients call, the database that holds the truth, the jobs that run without a user present, and the integrations with other systems. We take on new builds, extensions of live systems and rescues of backends that have become slow or hard to change. This page explains what that work covers, how we choose a stack, and how we run an engagement.
What does backend development include?
Our scope comes down to seven areas. Most projects touch four or five of them.
- APIs. REST for most public and partner interfaces, GraphQL when clients need flexible reads across many related objects. We version, document and test them as products, not as a side effect. Our REST vs GraphQL comparison shows how we decide.
- Data modelling. We design schemas on PostgreSQL first, with constraints, indexes and migrations that can run against a live database. Postgres covers relational data, JSON columns and full text search, so a second datastore needs a reason.
- Authentication and authorisation. Sessions or tokens, single sign on through SAML or OIDC for enterprise buyers, and role based access that is enforced on the server, not hidden in the UI.
- Queues and background jobs. Email, exports, webhooks, imports and anything slower than a request belongs in a worker with retries, backoff and a dead-letter store for failures.
- Integrations. Payments, CRMs, carriers, identity providers and legacy systems. Each connector gets one adapter with a shared error model, so one vendor outage does not spread.
- Observability. Structured logs, metrics, traces and alerts that page someone only when a budget is spent. We set this up in the first sprint, because it is hardest to add after an incident.
- Scaling and rewrites. Query tuning, caching, read replicas, and splitting a monolith into services when team size or load calls for it.
Which backend stack do we use?
We pick the stack for the product and the team who will own it after us.
| Choice | When it fits | Watch out for |
|---|---|---|
| Node.js with TypeScript, often NestJS | Product APIs, real-time features, teams that share types with a React frontend | CPU heavy work blocks the event loop; move it to workers |
| Python with Django or FastAPI | Data pipelines, machine learning, admin heavy products | Async code needs care to avoid blocking calls |
| Go | Small, high-throughput services, CLI tools, network code | A smaller hiring pool for product features |
We compare the first two in Node.js vs Python. If your team already runs a stack that works, we usually stay on it. Changing language rarely fixes a backend problem; a better boundary between modules usually does. When the question is bigger than one service, our software architecture work covers system design, domain boundaries and the monolith versus services decision.
Should we fix the backend or rewrite it?
Most rewrites fail because they stop shipping features for months and rebuild the same tangle in a new language. We fix in steps instead:
- Measure. Find the slow queries, the failing jobs and the modules that every change touches.
- Draw boundaries. Give each domain its own module and its own schema.
- Extract one domain. Route its traffic to the new code behind a feature flag, keep the old path as a fallback, then remove it once live traffic proves the new one.
- Repeat. Each extraction is reversible, so the team keeps releasing the whole time.
We rewrite from scratch only when the data model is wrong at its root, and we say so after the audit.
What have we built?
A US Series-B insurtech had a custom script for every carrier connection. We built a Node.js and PostgreSQL API platform with a connector SDK, so a new carrier went from roughly three weeks to three days and integration-related incidents dropped by about 40%.
A European marketplace ran on a decade-old PHP monolith. We extracted its five busiest domains into Node.js services in a strangler-fig migration: P95 API latency fell by about 65% and deploys became three times more frequent.
How do we run a backend engagement?
We start with a short audit of the repository, the database and the deploy pipeline, and write down scope, risks and a release plan. Work then runs in sprints inside your tooling, with code review on every change and CI from the first week. Handover is part of the plan: runbooks, architecture notes and tests that your engineers can read.
What the work costs to own depends on a few drivers: how many integrations you have, how much live data must be migrated, the traffic you must carry, and how much of the existing system stays. We scope it after the audit rather than guess.
For event-driven workloads that scale to zero, see serverless development.
If you are building a product company rather than a single API, see our SaaS development page. For websites and web applications in general, start from web development. To add engineers to your own team, hire backend developers.
