Backend Engineering & API Development ServicesThe product is fine. The layer under it is not.
We design and build the APIs, data models, and services underneath products that already run — so releases stop getting slower as load, integrations, and team size grow.
Why does every release take longer than the last?
The backend is rarely the thing anyone planned to rebuild. It becomes the constraint gradually, and then all at once.
- 01Estimates keep inflating and nobody can say why
- Every feature reaches into three places it should not, so a one-week change becomes three weeks of checking what else it breaks. The cost is not in the code that gets written, it is in the code nobody dares touch.
- 02The database is the bottleneck and nobody owns the schema
- It grew a migration at a time, with indexes added during incidents and columns nobody can explain. The queries that hurt are known by name, and avoided rather than fixed.
- 03Every integration is a bespoke one-off
- Each partner and vendor is wired directly into the product with its own retry logic and its own failure mode. A third party ships a change on a Friday and you find out from a customer.
These are not three problems. They are what happens when the data model and the service boundaries were never designed, only accumulated.
Designed to still be maintainable in year three.
The schema outlives your API, your framework, and usually your current team. We design it first and deliberately, because every shortcut taken there is paid for by every query written afterwards.
A specification, versioning, and documentation your consumers can build against without reading your source code. An undocumented API is an integration cost you keep paying on every new client.
We move systems incrementally behind a stable interface, so value ships in weeks and you can stop at any point. A full rewrite is a bet with no intermediate payoff, and most of them are lost quietly.
The same senior engineers own the deployment path, the observability, and the handover. "It works locally" is not the finish line when the team writing it is also the team on the call when it does not.
What backend engineering services does Devarithm offer?
Most engagements start with two or three of these rather than all six. If you are building a new product rather than fixing the layer under an existing one, SaaS product development is the page you want.
API Design & Documentation
The contract your product, your partners, and your future integrations build against — designed once, versioned deliberately, and documented so nobody has to read the implementation to use it.
- REST or GraphQL API design and conventions
- OpenAPI specification and generated documentation
- Versioning and deprecation policy
- Rate limiting, pagination, and error semantics
Data Modelling & Database Architecture
The part that is most expensive to change later and most often left to accumulate. We design the schema against how the data is actually read and written, then make the migration path to it safe.
- Schema design and normalisation review
- Index and query optimisation against real traffic
- Zero-downtime migration plan and execution
- Backup, retention, and archival strategy
Service Architecture & Decomposition
Boundaries drawn where the domain actually separates, not where the org chart does. Including the honest recommendation to stay with one well-structured service when that is the right answer.
- Service boundary and domain analysis
- Incremental decomposition plan
- Inter-service communication and event design
- Shared contract and schema governance
Authentication & Access Control
Identity, sessions, roles, and permissions built as a model rather than a growing pile of conditionals. This is the system that decides whether your next enterprise requirement is configuration or a quarter of work.
- Authentication and session architecture
- Role and permission model, enforced centrally
- SSO, OAuth, and multi-tenant access where needed
- Audit logging for sensitive operations
Third-Party Integration Layer
One place where external systems are spoken to, with retries, idempotency, and failure handling solved once instead of re-implemented per vendor.
- Integration layer with consistent retry and backoff
- Idempotency and reconciliation for financial or stateful calls
- Webhook ingestion, verification, and replay
- Vendor failure isolation and fallback behaviour
Performance & Reliability Engineering
Finding what is actually slow rather than what feels slow, then fixing it in the order that matters. Measurement first, because most performance work is spent on the wrong thing.
- Profiling and bottleneck analysis under real load
- Caching strategy and query optimisation
- Load testing against defined targets
- Instrumentation, tracing, and alerting
Not sure whether to refactor or rebuild?
Tell us where the system hurts — releases, queries, integrations, or all three. We will tell you what it takes to fix and in what order.
No commitment required. No pitch deck. Just a focused 30-minute conversation.
How does Devarithm rebuild a backend?
Five stages, ordered so you get something usable early. Nothing here requires you to stop shipping features while it happens.
- 01Week 1–2
Audit & Data-Flow Mapping
We read the codebase and the schema, trace how data actually moves, and measure where time is going under real traffic. You get a picture of the system as it is, not as the documentation claims.
You getSystem map, bottleneck analysis, and prioritised findings
- 02Week 2–3
API & Data Design
Schema, service boundaries, and API contracts designed against how the product actually behaves — with the migration path from what exists today written down before anything is built.
You getData model, API specification, and migration plan
- 03Week 3–8
Build & Incremental Migration
New services are built behind a stable interface and traffic is moved across a slice at a time, so every week produces something shippable and nothing requires a big-bang cutover.
You getWorking services in production, migrated incrementally
- 04Week 8–9
Harden & Instrument
Load testing against agreed targets, security review of the auth and permission surface, and instrumentation so the system reports its own health rather than waiting for a customer to.
You getVerified load targets, tracing, and alerting
- 05Week 9+
Handover & Support
Documentation your future engineers can actually use, a runbook for the failure modes we know about, and we stay on as the maintenance partner rather than disappearing at the handover meeting.
You getDocumentation, runbook, and ongoing support
What tech stack do we use for backend engineering?
Defaults, not dogma. Most of this work happens inside a stack that already exists, and we build on what is sound rather than rewriting it to suit us.
- Languages & Runtimes
- Node.jsTypeScriptPythonGo
- Frameworks
- NestJSExpressFastAPIDjango
- Data
- PostgreSQLMongoDBRedisElasticsearch
- APIs & Messaging
- RESTGraphQLOpenAPISQSKafka
- Platform
- AWSDockerTerraformGitHub Actions
It does transactions, JSON, full-text search, queues, and geospatial work well enough that most systems never need a second database. Every additional datastore is another thing to operate, back up, and keep consistent.
Microservices trade a code problem for a distributed-systems problem, and the second one is harder. We split when a boundary is real and the operational cost is justified, not because the architecture diagram looks better.
Schema, API contract, and client generated from one source of truth. A breaking change should fail in continuous integration, not in a customer-facing error at midnight.
Who is this service built for?
This is also a filter. If none of these describe you, the discovery call will be short and free, and we will tell you honestly.
- Products Outgrowing Their First Backend
- What was built to prove the idea is now carrying real customers, and every new feature costs more than the last one did.
- Boundaries, a designed data model, and an incremental path that does not stop feature work
- Teams With a Database Problem
- Queries are slow, the schema has grown by accretion, and the migrations everyone is afraid of keep getting postponed.
- Query and index work against real traffic, plus a zero-downtime migration executed for you
- Companies Opening an API to Partners
- Customers or partners want to integrate, and what exists internally was never designed to be exposed to anyone outside the team.
- A designed public API with a specification, documentation, versioning, and rate limiting
- Engineering Leads Without the Headcount
- You know exactly what the backend needs. You do not have two senior engineers free for three months to do it.
- Senior capacity on a scoped outcome, with your team retaining ownership throughout
Every engagement starts with the audit.
We read the codebase and the schema and measure where time is actually going, so the plan rests on evidence rather than on whichever part the team complains about most.
Thirty minutes to scope it, no obligation.
How can you engage Devarithm for backend work?
Indicative ranges for backend and API work. We give you a scoped figure after the audit, not before it — but you should not have to book a call to find out the order of magnitude.
A defined piece of work with a clear end state — a public API, a data-layer rebuild, a migration, or a decomposition.
- Fixed deliverables and fixed timeline
- Migration executed, not just planned
- Documentation and runbook included
- Best for: APIs, migrations, defined rebuilds
Ongoing senior backend capacity against a rolling priority queue, for teams shipping continuously.
- Monthly deliverables agreed upfront
- Rolling priority queue you control
- Performance and reliability work included
- Best for: sustained delivery without a hiring cycle
A fixed two-to-four week burst with a defined output, and no commitment past it.
- Fixed sprint window, fixed output
- No long-term commitment
- Best for: an audit, a performance rescue, one integration
What actually moves your number: codebase size and test coverage, whether the migration has to run live under production traffic, integration count, and any compliance requirements on the data.
Start with what is actually slowing you down.
Tell us where the system hurts — releases, queries, integrations, or all three. We will tell you what it takes to fix, in what order, and what it costs.
No commitment. No 50-slide deck. A focused 30-minute call.
Frequently Asked Questions
What is backend engineering?
Backend engineering is the design and construction of the server-side layer an application runs on — the APIs it exposes, the database and data model it stores state in, the services that hold business logic, and the authentication and integration layers around them. It is the part users never see and the part that decides how fast the product can change.
Do you work on an existing codebase or only build new ones?
Existing codebases are most of this work. Every engagement starts with an audit of what is there, and we migrate incrementally behind a stable interface rather than proposing a rewrite. If the honest answer is that something should be rebuilt, we show you the evidence first.
Should we move to microservices?
Usually not yet. Microservices trade a code-complexity problem for a distributed-systems problem, and the second is harder to operate. We split a service when a domain boundary is real and the operational cost is justified — and most teams get further by structuring one service properly.
How much does backend engineering cost?
Project-based backend work typically runs ₹4L–₹15L (roughly $5,000–$18,000). The main cost drivers are codebase size, whether a migration has to run live under production traffic, and how many external integrations are involved.
Can you migrate our database without downtime?
Yes, and that is the default approach. Zero-downtime migrations run through dual writes, backfill, and a staged read cutover, with a rollback path at every step. It takes longer than a maintenance window but does not require one.
Do you work alongside our existing engineering team?
Regularly. We work inside your repositories and your review process, and the design decisions are documented so your team can carry them forward. Your engineers keep ownership; we add senior capacity to a defined outcome.
What database do you recommend?
PostgreSQL for most systems. It handles transactions, JSON, full-text search, and queuing well enough that a second datastore is usually unnecessary, and every additional database is another thing to operate, back up, and keep consistent.
How do you handle API versioning?
Versioning and a deprecation policy are designed in at the start rather than invented when the first breaking change arrives. Consumers get a specification, documentation, and a defined window before anything they depend on is removed.
Who owns the code and the infrastructure?
You do, entirely. We work in your repositories and deploy to your accounts, and handover includes architecture documentation and a runbook. There is no proprietary layer that makes leaving us expensive.
Do you provide support after the work is delivered?
Yes. Lifetime support is the default engagement here rather than an upsell — ongoing maintenance, monitoring, performance work, and continued development as the system grows.
You might also need
Cloud & DevOps
The pipelines, infrastructure, and observability the backend runs on — usually scoped in the same engagement.
System Architecture
When the decision itself is still open, a short review costs far less than building the wrong thing well.
SaaS Product Development
When there is no product yet and the backend is one part of a build rather than the whole engagement.