Rapidly scale or downsize development capacity
Access to specialized, up-to-date Java expertise
Shorter hiring and onboarding cycle
Lower recruitment and HR overhead costs
Flexibility to engage talent only for project duration
Immediate productivity from pre-vetted professionals
Reduced long-term employment liabilities and benefits
Knowledge transfer to the in-house team
Ability to focus internal resources on core business tasks
Pay only for actual billable hours and deliverables
IntelliJ IDEA
Powerful IDE accelerating Java coding tasks
Apache Maven
Dependency management simplifying Java project builds
Gradle
Flexible build automation optimizing Java pipelines
JUnit
Robust testing framework ensuring reliable Java applications
Portfolios

Enterprise E-commerce Platform
Scalable B2C storefront powered by Java microservices.

Streaming Analytics Pipeline
Low-latency Kafka–Spark pipeline for actionable insights.

RESTful API Gateway
High-throughput gateway securing heterogeneous backend systems.

Supply-Chain Management Suite
Microservice solution optimizing inventory and logistics.

Payment Processing Engine
PCI-compliant engine enabling real-time transaction settlement.
Reviews
We’d spent six weeks chasing a full-stack Java developer. Smartbrain delivered two vetted Spring Boot & Hibernate pros in 10 days. Their onboarding packets and pre-configured IDE images let them commit to our loan-processing microservices on day one, boosting sprint velocity 28 % and cutting HR paperwork in half.
Melissa Hayes
HR Professional
Cascade FinTech Solutions
Smartbrain’s Java staffing saved our release. The new hire arrived fluent in Java 17, Kafka Streams, and Kubernetes; zero ramp-up. He refactored our data-pipeline REST APIs the first week, dropping JVM memory use 30 %. We finally hit feature freeze two sprints early.
Carlos Bennett
Dev Team Lead
NovaWave Analytics
As a scaling SaaS shop we needed senior Java microservices talent fast. Smartbrain shrank our hiring cycle from 60 days to 12 and handled all onboarding. The developers slotted into our pay-as-you-go billing module seamlessly, uplifting release quality and letting me focus on fundraising.
Rebecca Klein
CEO
HarborCloud Tech
Smartbrain’s contract Java devs blended into our legacy JPA/Struts stack without fuss. They automated builds with Gradle & Docker, cutting nightly compile time from 40 to 15 minutes. Support tickets dropped 22 %, and my in-house crew can finally tackle new IIoT features.
Daniel Price
Owner
IronGate Manufacturing Software
Hiring Java backend talent in Des Moines was brutal. Smartbrain tapped its nationwide pool and delivered three remote engineers adept at Spring Security and OAuth2. Their structured onboarding portal synced docs, tax forms, and git access in hours, slashing recruiting stress and boosting team throughput.
Linda Moore
HR Professional
Sunridge Insurance Systems
Tech Stacks
Spring Boot Microservices Stack
Spring Boot Microservices Stack blends Spring Boot, Spring Cloud, Maven or Gradle, Docker, and Kubernetes to let Java teams craft resilient distributed systems quickly. Spring Boot’s opinionated auto-configuration accelerates RESTful service creation while Spring Cloud adds service discovery, configuration management, circuit breakers, and gateway routing. Maven or Gradle handle dependency resolution and repeatable builds, Docker packages each microservice into portable containers, and Kubernetes orchestrates scalable deployments across clusters. The stack embraces twelve-factor principles, DevOps automation, and cloud-native patterns, reducing boilerplate and operational friction. It is extremely popular in enterprise modernization projects, especially when migrating monoliths incrementally. Developers deploy microservices confidently.
Jakarta EE Enterprise Stack
Jakarta EE Enterprise Stack centers on application servers such as WildFly, Payara, Open Liberty, or GlassFish delivering the standardized APIs formerly known as Java EE. It combines CDI, JPA, EJB, JAX-RS, JMS, Bean Validation, and Servlet technology to implement multilayered, transaction-safe business applications. Maven or Gradle manage project structure; Docker images simplify deployment; traditional relational databases like PostgreSQL or Oracle supply persistent storage. Built-in clustering, security realms, and thread management offload infrastructural concerns, allowing architects to focus on domain logic and portability. Long-term specifications, backward compatibility, and vendor neutrality make Jakarta EE attractive for regulated, mission-critical corporate systems worldwide enterprises.
Reactive and Event-Driven Stack
The Reactive and Event-Driven Stack empowers non-blocking, high-throughput services using frameworks like Spring WebFlux, Project Reactor, Vert.x, Netty, and Akka. It favors asynchronous data streams over thread-per-request models, achieving massive scalability with small resource footprints. Developers express data pipelines through publishers, subscribers, and back-pressure, while Kotlin coroutines or Java virtual threads sometimes complement reactive primitives. JSON over HTTP, WebSockets, or gRPC transport messages; Kafka or RabbitMQ provide durable event buses. Observability relies on metrics, distributed tracing, and reactive-friendly debugging tools. When coupled with cloud functions and serverless platforms, the stack enables responsive, resilient, real-time applications delivering sub-second user experiences today.
Android Development Stack (Java Edition)
Although Kotlin dominates new Android code, many Java developers still rely on the classic Android Development Stack consisting of Android SDK, Android Studio, Gradle build scripts, and libraries like Retrofit, Room, and Dagger/Hilt. The stack targets smartphones, tablets, wearables, televisions, and vehicle consoles. Java code interacts with Java-based APIs for activities, services, content providers, notifications, and UI widgets. Gradle handles multi-module builds, variant flavors, and continuous integration pipelines. Retrofit simplifies REST calls, Room abstracts SQLite persistence, and Dagger supplies dependency injection. Emulator images, Firebase services, and Google Play Console complete the lifecycle from prototyping through instrumentation testing to global distribution.
Big Data Processing Stack
The Big Data Processing Stack leverages Java APIs within Hadoop, Spark, Flink, and Kafka ecosystems to crunch petabyte-scale datasets. HDFS or cloud object storage houses raw information; YARN, Mesos, or Kubernetes schedule distributed jobs. Developers write Spark RDDs, DataFrames, or Flink streaming operators in pure Java, often using Lombok, Avro, and Jackson for model serialization. Kafka Connect ingests events, while Kafka Streams provides real-time aggregation pipelines. Parquet, ORC, and Iceberg optimize columnar persistence. Gradle or Maven create fat-jar or Docker artifacts deployable on EMR, Dataproc, or on-prem clusters. The stack underpins analytics dashboards, recommendation engines, fraud detection, and IoT telemetry.
Testing and CI/CD Stack
The Testing and CI/CD Stack equips Java developers with JUnit 5, TestNG, AssertJ, Mockito, JaCoCo, Maven or Gradle, Docker, Jenkins, GitHub Actions, and SonarQube to ensure code quality and delivery velocity. Unit, integration, contract, and end-to-end tests execute automatically on every commit, while test containers spin up ephemeral databases or message brokers. Code coverage metrics gate merges; static analysis highlights vulnerabilities and smells. Build scripts package artifacts, publish snapshots to Nexus or Artifactory, then trigger multi-stage pipelines deploying to staging and production clusters. Slack or Teams notifications provide feedback loops. The stack enforces automated governance, fostering confident, continuous, reliable releases.
Shortlist

Alexei Petrov
Principal Java Microservices Engineer

Carlos da Silva
Senior Java Cloud Developer

Vikram Mehta
Java Solution Architect

Jonas Becker
Java Reactive Engineer

David Ochieng
Java Backend Engineer

Marko Ignatovski
Lead Java Engineer / Ex-Engineering Manager
Dev augmentation service
Faster Time-to-Market
Augmenting your team with pre-vetted Java developers lets you skip lengthy recruitment and onboarding, so features ship sooner.
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Scalable Workforce on Demand
Quickly scale development capacity up or down as project demands fluctuate, paying only for the expertise you actually need.
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Access to Specialized Expertise
Staff augmentation brings in developers experienced with niche Java frameworks, performance tuning, and cloud integrations that your core team might lack.
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Cost-Efficient Resource Allocation
Avoid the overhead of full-time hires—no recruitment fees, benefits, or idle bench time—while still gaining senior-level talent.
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Reduced Project Risk
Reliable augmentation partners supply seasoned professionals who follow proven delivery processes, lowering technical and schedule risks.
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Knowledge Transfer & Upskilling
External senior Java engineers mentor in-house staff, introducing best practices, modern tooling, and improved code quality that remain after the engagement ends.
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Domain expertise
Financial Services & FinTech
Banks, trading platforms, payment gateways and insurance firms rely heavily on Java for building secure, low-latency and highly-scalable back-end systems that process millions of transactions every day.
E-commerce & Retail Technology
Online marketplaces, retail POS systems and order-fulfillment platforms use Java to power catalog management, payment processing, recommendation engines and microservice architectures that must remain available 24/7.
Telecommunications & Networking
Telecom operators depend on Java for building OSS/BSS solutions, real-time billing, network management and messaging services where portability and high throughput are critical.
Enterprise Software & SaaS
Large enterprises and SaaS vendors favor Java for ERP, CRM, HRM and other mission-critical applications because of its mature ecosystem, strong typing, scalability and long-term backward compatibility.
Why hire with us
Immediate access to experienced Java developers
Faster project kickoff and reduced time-to-market
Scalable team size that grows or shrinks with project needs
Lower hiring and onboarding costs compared with full-time staff
Reduced HR and administrative overhead (payroll, benefits, taxes)
Access to up-to-date best practices, frameworks, and tooling
Ability to fill niche skill gaps (e.g., Spring Boot, Microservices, Kafka)
Improved risk management through vendor SLAs and talent replacement
Fresh external perspectives that spur innovation and code quality
Enables in-house team to focus on core business features and strategy