Do you know

476,000 open tech positions exist in the US right now. Backend engineering roles account for more than 30% of unfilled developer seats.

Trusted by 150+ Enterprise Development Teams

Infosys TCS Capital One Honeywell Swiggy HCL Verizon
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•
SOC 2 Certified
•
Microsoft Microsoft Gold Partner
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95% Client Satisfaction

Enterprise backend Development

WHAT YOU CAN BUILD WITH BACKEND DEVELOPERS

Hire backend developers to solve the most expensive problem in software: systems that cannot scale when the business does. These are the servers, databases, and APIs your entire product depends on. A failure here means downtime, data loss, regulatory fines, or a product rewrite at the worst possible time. Our developers integrate with your existing team to deliver production systems that scale predictably, perform consistently, and pass audits when required.

Cloud-Native Microservices Architecture

Build distributed systems where individual services scale, fail, and deploy independently. Your current monolith creates deployment bottlenecks that cost you 3 releases per quarter. Our developers decompose services based on bounded contexts, implement event-driven communication with Kafka or RabbitMQ, and instrument every service for observability from day one. No big bang rewrites. We use the strangler fig pattern where it makes sense and domain-driven design where it does not. Your architecture becomes something you can explain to an investor and a board simultaneously.

Tech Stack:

Node.js Go Docker Kubernetes Kafka AWS ECS / EKS Istio Prometheus

Outcome

Independent deployments in under 8 minutes | Zero-downtime releases | Service mesh with full trace visibility

Regulatory Compliance Systems (HIPAA, SOC 2, GDPR)

Build systems where audit readiness is not a last-minute scramble. Compliance failures cost an average $4.45M per data breach (IBM Security 2023). That number assumes the breach does not also trigger regulatory action. Our developers implement RBAC at the data layer, build audit logging as a first-class concern, and architect data flows that satisfy GDPR data residency requirements without crippling performance. They have done this in healthcare, fintech, and legal SaaS. You get a system your compliance team can actually explain to auditors.

Tech Stack:

PostgreSQL (Row-Level Security) AWS KMS HashiCorp Vault Audit Log Pipelines Spring Security Node.js + NestJS

Outcome

SOC 2 Type II audit passed in 6 weeks | HIPAA-compliant data handling | Full audit trail with tamper-evident logging

Legacy Monolith Modernization

Migrate aging systems without the big-bang rewrite that kills most modernization projects. The IEEE estimates 73% of large-scale rewrites fail or get abandoned mid-project. Migrating too fast means data corruption. Too slow means your team maintains two systems indefinitely. Our developers use proven extraction patterns: strangler fig for incremental decomposition, anti-corruption layers to protect the new system from old data models, and blue-green deployments to cut over without downtime. Your monolith does not get replaced. It gets retired, one bounded context at a time.

Tech Stack:

Java Spring Boot Python Django PostgreSQL RabbitMQ Redis Docker AWS CodeDeploy

Outcome

Zero-downtime migration | 60% reduction in deployment risk | Legacy system retired in 18 months on average

Real-Time Event Streaming and Processing

Build systems that process millions of events per second without losing a single one. At high volume, every millisecond of processing delay compounds. A 50ms lag becomes a 50-second queue at 1,000 events/second. Our developers design for backpressure, implement exactly-once semantics where the business requires it, and separate the hot path from the cold path in your data architecture. They know when Kafka is the right tool and when a simple Redis stream is better. No over-engineering. The right solution for your volume.

Tech Stack:

Apache Kafka Apache Flink Redis Streams Go PostgreSQL ClickHouse Grafana + Loki

Outcome

500,000+ events/second throughput | Sub-100ms end-to-end latency | Exactly-once delivery with full audit trail

Enterprise API Platform and Integration Layer

Design the API layer that connects your product to partners, third-party systems, and internal services without turning into technical debt. Poorly designed APIs cost you the integrations your sales team promised and the partnerships your product team negotiated. Our developers design APIs using API-first principles, versioning strategies that do not break existing consumers, and rate limiting that protects your infrastructure from your most successful partners. For teams building developer-facing APIs, we also cover OpenAPI spec-first development and developer portal documentation. Our Node.js developers handle the API tier specifically for teams who need that depth.

Tech Stack:

REST GraphQL gRPC OpenAPI 3.0 Kong API Gateway AWS API Gateway Node.js / NestJS Postman

Outcome

API uptime 99.97% | Rate limiting at 100,000+ requests/minute | SDK and documentation delivery included

AI and ML Pipeline Integration

Build the backend infrastructure your AI features actually require. Most LLM integration failures are not model failures. They are retrieval failures, latency failures, and cost failures caused by backends that were not designed for AI workloads. Our developers build RAG pipelines with vector database retrieval, implement semantic caching to reduce LLM API costs by 40-60%, and design async inference queues that keep your product responsive while models compute. They have integrated OpenAI, Anthropic, and open-source models in production contexts where cold starts and token costs actually matter to the P&L. Teams wanting deeper Python ML expertise can explore our Python developer practice separately.

Tech Stack:

Python (FastAPI / Django) Pinecone / Weaviate LangChain Redis (Semantic Cache) AWS SageMaker OpenAI API Celery

Outcome

40-60% LLM cost reduction via semantic caching | Sub-200ms retrieval latency | Production AI features shipped in 4-6 weeks

Multi-Tenant SaaS Platform Engineering

Build the data isolation and tenant management infrastructure your SaaS product requires to go upmarket. Enterprise buyers will not sign contracts if your data model cannot guarantee tenant isolation. Our developers implement multi-tenancy at the right layer for your architecture: schema-per-tenant for strict isolation, row-level security for cost efficiency, or dedicated infrastructure for your largest enterprise accounts. They design the billing meter infrastructure, usage tracking, and feature flag systems that SaaS products need at every growth stage. None of this is optional when you are chasing Fortune 500 accounts.

Tech Stack:

PostgreSQL (Schema Isolation / RLS) Stripe Billing API LaunchDarkly / Unleash AWS Organizations Node.js / Python Redis

Outcome

Isolated tenant data architecture | SOC 2 compliant by design | Billing accuracy at 99.99%

Fintech Core Systems and Payments Infrastructure

Build payment processing, ledger systems, and transaction pipelines where correctness is non-negotiable. A rounding error in a ledger is not a bug. It is a compliance violation and a customer trust problem. Our developers implement double-entry bookkeeping in PostgreSQL, idempotent payment processing with Stripe or Adyen, and reconciliation pipelines that catch discrepancies before month-end close. They have built transaction systems that process millions of daily operations for Series B fintech companies with full PCI DSS alignment. For teams operating in fintech specifically, our fintech development practice covers the full regulatory context.

Tech Stack:

PostgreSQL (ACID Transactions) Stripe / Adyen Java Spring Boot Python Apache Kafka (Event Sourcing) AWS Lambda Vault for Secrets

Outcome

Zero financial discrepancies in 18 months | PCI DSS compliant architecture | 2M+ daily transactions with sub-50ms p99

Build distributed systems where individual services scale, fail, and deploy independently. Your current monolith creates deployment bottlenecks that cost you 3 releases per quarter. Our developers decompose services based on bounded contexts, implement event-driven communication with Kafka or RabbitMQ, and instrument every service for observability from day one. No big bang rewrites. We use the strangler fig pattern where it makes sense and domain-driven design where it does not. Your architecture becomes something you can explain to an investor and a board simultaneously.

Tech Stack:

Node.js Go Docker Kubernetes Kafka AWS ECS / EKS Istio Prometheus

Outcome

Independent deployments in under 8 minutes | Zero-downtime releases | Service mesh with full trace visibility

Build systems where audit readiness is not a last-minute scramble. Compliance failures cost an average $4.45M per data breach (IBM Security 2023). That number assumes the breach does not also trigger regulatory action. Our developers implement RBAC at the data layer, build audit logging as a first-class concern, and architect data flows that satisfy GDPR data residency requirements without crippling performance. They have done this in healthcare, fintech, and legal SaaS. You get a system your compliance team can actually explain to auditors.

Tech Stack:

PostgreSQL (Row-Level Security) AWS KMS HashiCorp Vault Audit Log Pipelines Spring Security Node.js + NestJS

Outcome

SOC 2 Type II audit passed in 6 weeks | HIPAA-compliant data handling | Full audit trail with tamper-evident logging

Migrate aging systems without the big-bang rewrite that kills most modernization projects. The IEEE estimates 73% of large-scale rewrites fail or get abandoned mid-project. Migrating too fast means data corruption. Too slow means your team maintains two systems indefinitely. Our developers use proven extraction patterns: strangler fig for incremental decomposition, anti-corruption layers to protect the new system from old data models, and blue-green deployments to cut over without downtime. Your monolith does not get replaced. It gets retired, one bounded context at a time.

Tech Stack:

Java Spring Boot Python Django PostgreSQL RabbitMQ Redis Docker AWS CodeDeploy

Outcome

Zero-downtime migration | 60% reduction in deployment risk | Legacy system retired in 18 months on average

Build systems that process millions of events per second without losing a single one. At high volume, every millisecond of processing delay compounds. A 50ms lag becomes a 50-second queue at 1,000 events/second. Our developers design for backpressure, implement exactly-once semantics where the business requires it, and separate the hot path from the cold path in your data architecture. They know when Kafka is the right tool and when a simple Redis stream is better. No over-engineering. The right solution for your volume.

Tech Stack:

Apache Kafka Apache Flink Redis Streams Go PostgreSQL ClickHouse Grafana + Loki

Outcome

500,000+ events/second throughput | Sub-100ms end-to-end latency | Exactly-once delivery with full audit trail

Design the API layer that connects your product to partners, third-party systems, and internal services without turning into technical debt. Poorly designed APIs cost you the integrations your sales team promised and the partnerships your product team negotiated. Our developers design APIs using API-first principles, versioning strategies that do not break existing consumers, and rate limiting that protects your infrastructure from your most successful partners. For teams building developer-facing APIs, we also cover OpenAPI spec-first development and developer portal documentation. Our Node.js developers handle the API tier specifically for teams who need that depth.

Tech Stack:

REST GraphQL gRPC OpenAPI 3.0 Kong API Gateway AWS API Gateway Node.js / NestJS Postman

Outcome

API uptime 99.97% | Rate limiting at 100,000+ requests/minute | SDK and documentation delivery included

Build the backend infrastructure your AI features actually require. Most LLM integration failures are not model failures. They are retrieval failures, latency failures, and cost failures caused by backends that were not designed for AI workloads. Our developers build RAG pipelines with vector database retrieval, implement semantic caching to reduce LLM API costs by 40-60%, and design async inference queues that keep your product responsive while models compute. They have integrated OpenAI, Anthropic, and open-source models in production contexts where cold starts and token costs actually matter to the P&L. Teams wanting deeper Python ML expertise can explore our Python developer practice separately.

Tech Stack:

Python (FastAPI / Django) Pinecone / Weaviate LangChain Redis (Semantic Cache) AWS SageMaker OpenAI API Celery

Outcome

40-60% LLM cost reduction via semantic caching | Sub-200ms retrieval latency | Production AI features shipped in 4-6 weeks

Build the data isolation and tenant management infrastructure your SaaS product requires to go upmarket. Enterprise buyers will not sign contracts if your data model cannot guarantee tenant isolation. Our developers implement multi-tenancy at the right layer for your architecture: schema-per-tenant for strict isolation, row-level security for cost efficiency, or dedicated infrastructure for your largest enterprise accounts. They design the billing meter infrastructure, usage tracking, and feature flag systems that SaaS products need at every growth stage. None of this is optional when you are chasing Fortune 500 accounts.

Tech Stack:

PostgreSQL (Schema Isolation / RLS) Stripe Billing API LaunchDarkly / Unleash AWS Organizations Node.js / Python Redis

Outcome

Isolated tenant data architecture | SOC 2 compliant by design | Billing accuracy at 99.99%

Build payment processing, ledger systems, and transaction pipelines where correctness is non-negotiable. A rounding error in a ledger is not a bug. It is a compliance violation and a customer trust problem. Our developers implement double-entry bookkeeping in PostgreSQL, idempotent payment processing with Stripe or Adyen, and reconciliation pipelines that catch discrepancies before month-end close. They have built transaction systems that process millions of daily operations for Series B fintech companies with full PCI DSS alignment. For teams operating in fintech specifically, our fintech development practice covers the full regulatory context.

Tech Stack:

PostgreSQL (ACID Transactions) Stripe / Adyen Java Spring Boot Python Apache Kafka (Event Sourcing) AWS Lambda Vault for Secrets

Outcome

Zero financial discrepancies in 18 months | PCI DSS compliant architecture | 2M+ daily transactions with sub-50ms p99

DO YOU KNOW

Developers spend an average 32% of their week in meetings. At a 40-hour week, that is 12.8 hours of non-coding time. A $140,000/year developer delivers approximately $95,000 in actual coding value.

32% of developer time is lost in meetings

Atlassian 2024 Developer Report

Developer Capabilities

TECHNICAL EXPERTISE OUR BACKEND DEVELOPERS BRING

Our backend developers average 7.8 years of production experience across distributed systems, cloud-native architecture, and regulated industry applications. Every developer is vetted for system design thinking and debugging under pressure, not just syntax proficiency. We reject developers who have only tutorial experience regardless of how well they interview.

7.8 yrs Avg Experience
68% AWS Certified
54% GCP Certified
85%+ Test Coverage Std
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Server-Side Language and Framework Mastery

Your backend developers are only as reliable as their understanding of concurrency, memory management, and the runtime behavior of the language they write in. Bugs at this level do not show up in unit tests. They show up at 2am during a traffic spike. Our developers have shipped production systems in Node.js with the Express and NestJS frameworks, Python with Django and FastAPI, Java with Spring Boot, and Go for high-throughput services. They understand event loop behavior in Node.js, GIL implications in Python, JVM warm-up in Java, and goroutine scheduling in Go. They pick the right language for the constraint, not the one they are most comfortable with.

Node.js 20+ Python 3.11+ Java 21 (LTS) Go 1.22 NestJS FastAPI Spring Boot 3.x Gin
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Cloud Platform Integration (AWS, GCP, Azure)

Cloud is not just infrastructure. It is architecture. The wrong AWS service choice at the design phase costs you six months of performance debugging later. Our developers have deployed production workloads on AWS (EC2, ECS, EKS, Lambda, RDS, DynamoDB, SQS, SNS), GCP (Cloud Run, Pub/Sub, BigQuery, Spanner), and Azure (AKS, Azure Functions, CosmosDB, Service Bus). They are not just YAML writers. They understand cost optimization, auto-scaling behavior, and VPC design. 68% hold active AWS certifications. They design for cloud from the first line of code.

AWS (EKS, RDS, Lambda, SQS, SNS, CloudFront) GCP (Cloud Run, Pub/Sub, BigQuery) Azure (AKS, Functions) Terraform AWS CDK
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Database Architecture and Optimization

The database is where most backend performance problems live. Not in the application code. Our developers profile query execution plans before writing the ORM query. They know when a PostgreSQL partial index eliminates a full table scan, when Redis caching makes more sense than database optimization, and when DynamoDB single-table design is worth the complexity tradeoff. They have optimized queries that went from 4-second response times to 40 milliseconds. They understand ACID guarantees in PostgreSQL, eventual consistency tradeoffs in MongoDB, and TTL patterns in Redis. Write once, understand forever.

PostgreSQL 15+ MySQL 8.0 MongoDB 7.0 Redis 7.x DynamoDB ClickHouse Prisma SQLAlchemy Hibernate
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API Design and Protocol Expertise

An API is a contract. Breaking changes in a versioned API cost you partner integrations worth more than the developer time you saved. Our developers design APIs with consumer needs as the first constraint, not implementation convenience. They implement OpenAPI 3.0 spec-first development, GraphQL schemas with proper N+1 prevention using DataLoader, gRPC services with Protocol Buffer versioning, and WebSocket connections with reconnection logic. They document everything. They version thoughtfully. They deprecate with notice. Your API becomes an asset, not a liability.

REST (OpenAPI 3.0) GraphQL (Apollo Server) gRPC (Protocol Buffers) WebSocket Kong AWS API Gateway Swagger UI
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Testing, Quality Assurance and Reliability

85% test coverage is the floor, not the ceiling. Our developers write unit tests, integration tests, and contract tests as a default. They do not write tests after code is shipped. Load testing with k6 or Locust runs before deployment to production. They implement chaos engineering patterns for services where uptime SLAs matter. They write tests that catch regressions, not just tests that make coverage metrics look good. Code review includes performance implications, not just correctness. Reliability is an engineering discipline, not a QA responsibility.

Jest Pytest JUnit 5 Testcontainers k6 Locust WireMock Pact (Contract Testing) SonarQube
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DevOps, CI/CD and Infrastructure as Code

Developers who cannot ship are a bottleneck. Our backend developers configure their own CI/CD pipelines. They do not wait for a separate DevOps team to unblock them. They write Terraform modules, configure GitHub Actions workflows, and set up Docker multi-stage builds that reduce image sizes by 60% or more. They understand blue-green deployment, canary releases, and feature flag-based rollouts. Infrastructure as code means every environment is reproducible. No snowflake servers. No manual configuration drift. Production and staging behave the same because they are built the same way.

Docker Kubernetes 1.29+ Terraform 1.7+ GitHub Actions Jenkins ArgoCD Helm AWS CDK Datadog New Relic
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Security, Authentication and Compliance Engineering

Security is not a feature you add after launch. Our developers implement JWT authentication with proper token rotation, OAuth 2.0 / OIDC flows for SSO, and API key management with rate limiting and usage tracking. They sanitize inputs at the boundary, not in the middle of the stack. They implement secrets management using HashiCorp Vault or AWS Secrets Manager instead of environment variables in plain text. They write code that passes OWASP Top 10 audits. For regulated industries, they design data flows that satisfy GDPR right-to-erasure requirements and HIPAA minimum-necessary access standards. Security is an architecture decision, not a checkbox.

JWT OAuth 2.0 / OIDC HashiCorp Vault AWS Secrets Manager OWASP ZAP Snyk Keycloak Auth0 AWS IAM

BACKEND PLATFORM EVOLUTION : WHY IT MATTERS FOR YOUR PROJECT

Backend engineering is not a static discipline. The systems you build today on the same patterns used in 2015 will be production incidents by 2027. Understanding where the backend ecosystem is and where it is going helps you make architecture decisions that age well. Here is how the landscape has matured and what it means for your current project.

2000-2010

Monolithic Era

Legacy Support

LAMP stacks, Spring MVC, and Rails dominated. Everything lived in one deployable. Teams shipped once a month because the risk of deployment was too high. Systems that still run on these patterns carry significant deployment and scaling debt. We can work with them while migrating incrementally.

2010-2015

SOA and REST Standardization

Foundation

Service-Oriented Architecture introduced separation, but integration complexity was high. JSON over HTTP became the lingua franca. REST APIs replaced SOAP across most new projects. This era established the patterns most current teams still build on. Developers without this context misdesign APIs that look RESTful but behave like RPC.

2015-2019

Microservices and Container Revolution

Maturing

Docker and Kubernetes made microservices operationally feasible. Teams that adopted this era's patterns without the operational maturity to support them created distributed monoliths instead. Our developers have seen both versions and know the difference. Container-native development is now the default expectation for new projects.

2020-2023

Cloud-Native and Serverless Adoption

Current LTS

AWS Lambda, Cloud Run, and serverless frameworks reduced operational overhead but introduced cold start latency and state management complexity. Event-driven architecture with Kafka and SQS became standard for decoupled systems. Most enterprise backends built after 2020 use a hybrid of containerized services and serverless functions.

2024+

AI-Integrated Backend Systems

Latest Stable

LLM integration, vector databases, and RAG pipelines are now production requirements across SaaS, fintech, and healthcare. Backend developers who cannot build AI infrastructure are a constraint. Our developers have shipped production AI features including semantic search, document processing pipelines, and LLM-powered automation with real cost management.

Technology Fit Assessment

WHEN BACKEND ENGINEERING IS THE RIGHT INVESTMENT (AND WHEN IT IS NOT)

Backend development covers a wide range of specializations. Hiring a generalist backend developer for a real-time trading system or a compliance-heavy healthcare platform is a mismatch that will cost you more than starting over. Here is when to invest in dedicated backend engineers versus when a different approach makes more sense.

Choose Dedicated Backend Engineers When

  • If your product needs to handle more than 10,000 concurrent users, serve multi-region traffic, or process transactions where failure costs real money, choose backend specialists. This applies to e-commerce at Series A and above, fintech at any stage, and SaaS products targeting enterprise buyers. A full-stack generalist writing backend code for these systems is technical debt accumulating at $100K per year.

  • HIPAA, SOC 2 Type II, PCI DSS, and GDPR are not compliance boxes your full-stack team checks after launch. They are architectural decisions made at the schema design stage. Healthcare, fintech, legal tech, and government SaaS products require backend engineers who have passed audits before. Not developers who have read about audits.

  • If you are debugging performance issues with a DBA, duct-taping caches to slow queries, and your senior engineer's calendar looks like an incident postmortem calendar, you need backend specialists. Generalists can build. Specialists can fix production systems without taking the product offline.

  • Migrating a monolith to microservices, re-platforming from on-premise to cloud, or introducing event-driven patterns to a CRUD-heavy codebase are projects where experience is irreplaceable. The risk of getting it wrong is measured in months of regression and lost engineering velocity.

When Dedicated Backend Engineers Are NOT the Right Fit

  • If your product is a content-managed website, an internal admin tool, or a simple form-to-database application, a full-stack developer or a no-code platform is more appropriate. Dedicated backend engineers are expensive for work that does not require their depth. We will tell you this directly rather than take your budget for a project that does not need us.

  • Backend engineers need 2-3 weeks to ramp up on your codebase before they add net-positive velocity. Engagements shorter than 3 months rarely recover the ramp-up cost. If your timeline is weeks, not months, consider a freelance platform instead.

  • If your primary constraint is user interface, design systems, or frontend performance, invest there first. Backend infrastructure without a product users actually want is infrastructure debt.

  • Quality backend engineers at enterprise production standards do not exist at freelance platform rates. If budget is the primary constraint, junior local developers with close supervision or bootcamp partnerships offer a better risk profile than unvetted offshore candidates at rock-bottom rates.

Ask yourself: What breaks if the backend cannot handle 10x today's traffic? If the answer is 'everything,' you need specialists. The right choice depends on your current scale, compliance obligations, and the consequences of failure. We have delivered 2,000+ projects across multiple languages and frameworks. We will tell you honestly whether we are the right fit for yours.

"

"Their backend engineers perform at very high standards. The team we integrated rewrote our payment processing pipeline in 8 weeks without a single production incident. We have had a strong relationship for almost 3 years."

The best partnerships are the ones you do not have to worry about. Technical execution and reliable delivery compound over time. Three years is not a contract length. It is a track record.

Marcus T.

Series C Fintech Platform

EVP of Engineering

Built for Technical Leaders

WHY FORWARD-THINKING CTOS CHOOSE HIREDEVELOPER

500+
Developers Placed
2,000+
Projects Delivered
40%
Efficiency Gain
5 Stars
Client Satisfaction

We do not hire developers who finished a backend bootcamp last month. Our candidates have shipped distributed systems in production domains where latency, compliance, and uptime determine business outcomes. Every candidate completes a take-home assignment involving system design, concurrency handling, and database optimization, not fizzbuzz. Top 1% acceptance rate. Average accepted candidate: 7.8 years of experience. We reject more candidates per month than most agencies hire per quarter.

Your projects ship 40% faster because our developers understand N+1 query problems, connection pool exhaustion, and async processing bottlenecks before they write the first line of code. They profile before optimizing. They benchmark every critical path. They write database queries that the query planner actually uses efficiently. No guessing. Every optimization is measured.

We maintain specialists for Node.js, Python, Java, and Go backends. Developers understand event loop behavior, garbage collection implications, and cloud-native design patterns. They have deployed APIs handling 50,000+ requests per second, systems with sub-10ms p99 latency, and multi-region architectures with automatic failover. Production veterans, not tutorial graduates.

Every engagement starts with an architecture review. We map your existing system, identify integration points, and understand your deployment patterns before writing code. Developers join your standups, use your tools, follow your workflows. Your team expands. It does not fragment.

ISO 27001 certified. SOC 2 Type II available on request. Zero security incidents in 3 years. 47+ enterprise audits passed. $2M professional liability plus $1M E&O plus cyber insurance coverage. Background checks on every developer: criminal, education, employment verification.

4-8 hours overlap with US, EU, or APAC time zones. Core hours availability for standups and code reviews. Async handoffs documented. You see commits daily, not monthly. No black box development.

Dedicated team at monthly rate. Staff augmentation for your existing team. Hourly for overflow work. Scale up with 1-2 weeks notice. Scale down with 2 weeks notice. No long-term contracts required.

If a developer does not meet your expectations within the first two weeks, we replace them at no additional cost. We also conduct regular check-ins to address concerns before they become problems.

TEAM INTEGRATION

HOW OUR BACKEND DEVELOPERS INTEGRATE WITH YOUR TEAM

Realistic timeline from first contact to production code

12 Days from 'hello' to code in production
Day 1-2 Requirements call + tech stack review + team structure mapping
Day 3-4 Developer profiles shared, you interview candidates, technical assessment
Day 5 Agreements signed, Day 0 setup begins (access provisioning)
Day 6-7 Developer joins standups, reviews codebase, aligns on conventions
Day 8-12 First production PR merged, code review completed, ongoing iteration
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Discovery

  • Requirements call
  • tech stack review
  • team structure mapping
icon

Matching

  • Developer profiles shared
  • you interview candidates
  • technical assessment
icon

Onboarding

  • Developer joins standups
  • reviews codebase
  • aligns on conventions
icon

Shipping

  • First production PR merged
  • code review completed
  • ongoing iteration
Start Your Team Integration

HOW WE USE AI IN DELIVERY

AI-POWERED DEVELOPMENT

Faster Shipping, Not Replacement

Our developers use AI as an acceleration tool, not a crutch...

using copilot GitHub Copilot
20-30% faster code completion

Boilerplate code, test scaffolding, documentation stubs

Architecture decisions, security-critical code, business logic
cursor ai Cursor AI
3 weeks to 2 weeks ramp time

Codebase Q&A, context-aware suggestions, onboarding acceleration

Critical feature implementation, production debugging without verification
chatgpt ChatGPT / Claude
Faster unblocking on research tasks

API documentation lookup, debugging patterns, code explanation

Unverified copy-paste, direct production deployment
Tabnine
Privacy-first for sensitive codebases

IP-sensitive projects, local model inference, air-gapped environments

Replacing human judgment, architecture decisions

How AI Actually Speeds Development

AI Does Well (We Use)
  • Documentation generation
  • Test case scaffolding
  • Boilerplate code completion
  • Code explanation and commenting
  • Regex and SQL generation
  • Repetitive refactoring patterns
AI Struggles (Humans Handle)

Real Impact on Your Project

Measured Q4 2024 across 50+ projects

45% Docs Faster
40% Tests Faster
30% Refactoring Faster
25% Feature Dev Faster
15% Debug Faster

ENTERPRISE SECURITY

SECURITY AND IP PROTECTION

Enterprise-grade security for regulated industries

secure testing and quality assurance
ISO 27001:2013
Certified
project on time
SOC 2 Type II
Available
assured
0 Incidents
in 3 Years
file
47+ Enterprise
Audits Passed
secure and protectected
$2M + $1M E&O +
Cyber Insurance

Code ownership assigned to you before repository access is granted. Work-for-hire agreements standard. No retained rights. Your code is your code. We sign NDAs on day one, not after negotiation.

Criminal background check, education verification, employment history validation, reference checks on every developer without exceptions. Reports available on request.

Secure office facilities with monitored access. Dedicated devices for client work. USB ports disabled. Screen recording available for compliance-sensitive projects where client audit requirements demand it.

MFA required for all systems. VPN-only access to client infrastructure. 4-hour access revocation guarantee on engagement end. Role-based permissions reviewed monthly.

Full code handover at engagement end. No vendor lock-in. Complete documentation transfer. Knowledge transfer sessions included. You walk away with everything.

Backend Developers Pricing & Rates

Real Rates, Real Experience

We focus on Exprience+
Junior

Entry Level

1-3 years experience

$2.5-$3.5K /month /month

Needs supervision.

Click to See Skill

Skill

  • Component creation
  • Template syntax
  • Basic routing
  • Angular CLI usage
Click to flip back
WE SHIP

Experienced

4-7 years experience

Works independently /month

Works independently

Click to see skills

Skill

  • Reactive Forms
  • RxJS operators
  • Lazy loading
  • Unit testing with Jest
Click to flip back
WE SHIP

Expert

8+ years experience

$6-8.5K /month /month

Mentors team

Click to see skills

Skill

  • NgRx state management
  • Performance optimization
  • CI/CD pipelines
  • System design
Click to flip back
WE SHIP

Architect

10+ years experience

$8.5-12K+ /month /month

Owns architecture

Click to see skills

Skill

  • Micro frontend architecture
  • Platform engineering
  • Team leadership
  • Enterprise patterns
Click to flip back

We focus on senior and lead engineers who ship. For projects requiring junior developers with heavy supervision, we recommend local contractors or bootcamp partnerships where you can provide that oversight directly.

See full pricing breakdown

TRANSPARENT PRICING

WHAT IS INCLUDED IN THE RATE

$5,500/month Senior Backend Developer

$ $5,500/month /mo
Developer Compensation: $3,200
Benefits (health, PTO, insurance): $800
Equipment (laptop, monitors): $200
Infrastructure (office, internet): $400
Management overhead: $600
Replacement insurance: $300
white user icon
$3,200
Developer Compensation
58%
right tick
$800
Benefits and Insurance
15%
gray equipment
$200
Equipment and Software
4%
$400
Infrastructure and Tools
7%
user gray icon
$600
Management Overhead
11%
secure testing and quality assurance
$300
Replacement Insurance
5%
No Hidden Fees
No Setup Fees
No Exit Fees
Our Rate

HireDeveloper: $5,500/month Senior

$5,500/month
  • Predictable monthly cost
  • All-inclusive (no hidden fees)
  • Full-time dedicated resource
  • Replacement guarantee included
  • Management and QA included
  • One invoice, one relationship
Predictable. Transparent.
VS
Other Offshore

$25/hour freelancer = ~$4,000 advertised/hr Freelancer

$25/hour /month
  • Add onboarding time (unbilled but real)
  • Add management overhead (your time)
  • Add rework cycles (quality variance)
  • Add replacement costs (when they leave)
  • Reality: $6,000+ effective monthly cost
High risk. Hidden costs...
The cheapest option is rarely the most economical. For the full cost breakdown of hiring backend developers, including hidden costs and real total cost of ownership, see our backend developer cost guide.

CLIENT CASE STUDIES

RECENT OUTCOMES

Three engagements from the past 18 months. For more case studies, see our dedicated developers service page.

The Challenge

  • Payment processing pipeline handling 80,000 daily transactions was failing under peak load with 3-5 second p99 latency
  • Monolithic architecture made every deployment a risk event: 4-hour freeze windows, 6 rollbacks in 6 months
  • New enterprise contracts required PCI DSS compliance within 90 days or risk losing the revenue

Our Approach

  • Week 1-2: Architecture review, identified 3 critical N+1 query patterns and connection pool exhaustion as root causes
  • Week 3-6: Extracted payment service from monolith using strangler fig, implemented idempotent processing with Kafka
  • Week 7-12: PCI DSS alignment, penetration test, performance load test to 500,000 daily transactions

Verified Outcomes

3.2s → 38ms Payment p99 latency reduced
Day 11 First production deployment post-onboarding
–6 weeks PCI DSS audit passed ahead of contract deadline

"They understood our constraints before we finished explaining them. The payment pipeline rewrite happened in 8 weeks without a single production incident. That is not normal. We renewed for a second year immediately."

VP of Engineering, Series B Fintech Platform

The Challenge

  • Series A healthcare SaaS targeting hospital system buyers, none would sign without SOC 2 Type II evidence
  • Existing backend had no audit logging, PHI was stored without encryption at rest, access controls were role-based in name only
  • 12-week window before a major health system procurement decision that represented $2.4M ARR

Our Approach

  • Week 1-2: Full security architecture review, gap analysis against SOC 2 Trust Services Criteria
  • Week 3-8: Implemented audit logging as event stream, PHI encryption with AWS KMS, RBAC at the PostgreSQL row-security level
  • Week 9-12: Penetration test remediation, evidence collection, auditor-ready documentation

Verified Outcomes

Week 11 SOC 2 Type II audit passed ahead of schedule
Zero critical Penetration test findings (2 medium, resolved in 48 hours)
$2.4M / 3 weeks Enterprise contract signed post-audit

"This team understood what a SOC 2 auditor actually looks for, not just what the checklist says. The difference is significant."

CTO, Series A Healthcare SaaS

The Challenge

  • 9-year-old PHP monolith serving 2M monthly users could not handle traffic spikes above 3x baseline, causing cart abandonment during sales events
  • Engineering team of 14 could not make meaningful progress on modernization while maintaining the existing system
  • Stakeholders had approved a 12-month roadmap, but two previous teams had failed to deliver on similar commitments

Our Approach

  • Month 1: Identified highest-value extraction target: product catalog and inventory service (most read-heavy, easiest bounded context)
  • Month 2-4: Extracted catalog service to Node.js microservice with Redis caching layer, zero downtime via traffic shadowing
  • Month 5-9: Cart and checkout extracted, event sourcing implemented for order state, load test to 15x baseline traffic

Verified Outcomes

11× load Black Friday handled with zero incidents (vs 3 outages prior year)
Monthly → Daily Deployment frequency increased (22 in week 12)
–2 months Legacy monolith retired ahead of 12-month schedule

"Two previous teams said they could do this. These developers actually delivered. The migration happened without a single customer-visible incident across 14 deployments."

Head of Engineering, 2M Monthly Active Users

QUICK FIT CHECK

Are We Right For You?

Answer 5 quick questions to see if we're a good match

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Question 1 of 5

Is your project at least 3 months long?

Offshore teams need 2-3 weeks to ramp up. Shorter projects lose 25%+ of timeline to onboarding.

FROM OUR EXPERTS

What We're Thinking

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FREQUENTLY ASKED QUESTIONS ABOUT HIRING BACKEND DEVELOPERS

How quickly can I hire backend developers through HireDeveloper?

We match you with pre-vetted backend developers within 48 hours of receiving your requirements. After you interview and approve candidates, typically 1-2 days, developers can start onboarding within 5 days. Most teams have their first production PR merged by Day 12. This assumes you have requirements documented. If you need help defining requirements, add 3-5 days for a discovery sprint. The total time from first conversation to code in production is 12 days when both sides are prepared.

What is your vetting process for backend developers?

Four-stage vetting: (1) Technical assessment covering backend fundamentals plus advanced topics including system design, concurrency patterns, database optimization, and API security. (2) Live coding interview with system design component for senior roles, including architecture scenarios from their claimed domain. (3) English communication assessment via video call. (4) Background verification: criminal, education, employment history. Top 1% of applicants pass. Average experience of accepted candidates: 7.8 years. We reject developers who have only tutorial or bootcamp experience regardless of how well they interview on syntax questions.

Can I interview developers before committing?

Yes, always. We share 2-3 candidate profiles with detailed technical backgrounds, project history, and communication samples. You conduct your own interviews however you prefer: technical screens, pair programming sessions, system design discussions. No commitment until you approve. If none of the candidates fit, we source additional candidates at no cost. You are hiring for your production systems. We accelerate the search but never force a fit.

How much does it cost to hire a backend developer?

Monthly rates by experience level: Junior (1-3 years) $2,500-$3,500, Mid-level (4-7 years) $3,500-$5,000, Senior (8+ years) $5,000-$7,000, Lead/Architect (10+ years) $7,000-$10,000+. All rates are fully loaded: compensation, benefits, equipment, infrastructure, management, and replacement insurance. No hidden fees. No setup costs. The rate you see is the rate you pay. For a complete breakdown of what drives backend developer cost, see our backend developer cost guide.

What is included in the monthly rate?

Everything required for the developer to be productive from day one: base salary and local benefits, health insurance, equipment (laptop, monitors, peripherals), software licenses and developer tools, secure office infrastructure with monitored access, management overhead for HR and payroll, and replacement insurance that covers our 2-week guarantee. You pay one predictable monthly amount. We do not charge for onboarding, knowledge transfer sessions, or reasonable scope clarification calls.

Are there any hidden fees or setup costs?

No. Zero setup fees. Zero onboarding charges. Zero surprise invoices. The monthly rate covers everything for standard engagements. If you need additional services like dedicated project management beyond developer-level coordination, specialized compliance training for specific regulatory frameworks, or on-site visits for audit purposes, we quote those separately and upfront before you commit. More than 90% of our clients use standard engagements with no add-ons.

What backend technologies and frameworks do your developers work with?

Our backend developers work with the current production-stable versions of Node.js (20 LTS+), Python (3.11+), Java (21 LTS), and Go (1.22+). Framework expertise includes NestJS, Express, FastAPI, Django, Spring Boot 3.x, and Gin. Database experience covers PostgreSQL 15+, MySQL 8.0, MongoDB 7.0, Redis 7.x, DynamoDB, and ClickHouse. Cloud certifications: 68% AWS certified, 54% GCP certified, 42% Azure certified. We match developers to your specific version requirements. If you are on an older version for compliance or stability reasons, we have developers with that specific experience.

Can your developers work with our existing tech stack?

Yes. During discovery we map your current technologies, deployment patterns, CI/CD pipeline, and integration points. We prioritize developers with direct experience in your exact stack. If an exact match is unavailable, which is rare for common stacks, we select developers with adjacent experience and provide 1-week targeted ramp-up. You approve the match before we start. We do not force-fit developers into stacks they do not know, and we will tell you directly if we cannot match your requirements accurately.

What is the minimum engagement period?

We recommend 3 months minimum. This accounts for the 2-3 week ramp-up period and ensures you get meaningful delivery value. Shorter engagements are possible for tightly scoped work, such as a specific integration audit or a defined migration sprint, but require upfront definition of scope and success criteria. Month-to-month billing is available after the initial 3-month period. We do not lock you into annual contracts.

Can I scale the team up or down?

Yes, with reasonable notice. Scale up: 1-2 weeks notice, as we maintain a pre-vetted bench for common backend technologies. Scale down: 2 weeks notice, which allows proper handoff documentation and knowledge transfer. No penalties for team size changes. If you need to scale to zero because the project ends, 2 weeks notice and we handle the clean exit: full code handover, documentation transfer, and knowledge transfer sessions with your remaining team. You are never stuck.