[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-java-software-engineering-jobs":3},{"Slug":4,"job_category":5,"Meta":6,"Intro":9,"Header":12,"OpenRoles":152,"Keywords":198,"Ques":244},"java software engineering jobs","Software Engineering",{"title":7,"description":8},"java software engineering jobs | 2026 Remote jobs","Explore java software engineering jobs with Spring Boot, microservices, and LLM training pipelines. Discover remote, senior, and entry-level roles on Rex.zone.",{"content":10,"approx_word_count":11},"Java software engineering jobs are a core technology entity: JVM-based backend development that powers microservices, data platforms, and AI-enabled products. On Rex.zone, these roles span Spring Boot APIs, distributed systems, cloud-native deployments, and ML-adjacent workflows like RLHF instrumentation, data labeling integrations, model evaluation telemetry, and content safety pipelines. Apply to remote, contract, full-time, and freelance openings aligned with modern AI\u002FML training workflows, including prompt evaluation services, named entity recognition pipelines, computer vision annotation backends, and large language model evaluation tools. Rex.zone is your navigational hub to discover Java roles across AI labs, tech startups, BPOs, and annotation vendors with clear requirements, transparent compensation, and fast application flows.",112,{"title":13,"desc":14,"content":15},"Java Software Engineering Jobs at Rex.zone","Find remote and on-site Java roles across microservices, cloud-native platforms, and AI workflow integrations. Apply fast, compare employers, and grow your JVM career.",[16,28,40,52,64,75,84,93,105,114,123,133,142],{"h2":17,"desc":18,"bullets":19},"About the Role","Java software engineering jobs focus on building scalable services, APIs, and data pipelines on the JVM. Teams use Spring Boot, Kotlin\u002FJava, and cloud-native platforms to deliver reliable microservices for high-throughput applications. Increasingly, Java engineers contribute to AI product infrastructure: integrating data labeling tools, RLHF feedback collection services, content safety moderation pipelines, prompt evaluation dashboards, named entity recognition processing services, and computer vision annotation backends that ensure training data quality and model performance improvement.",[20,21,22,23,24,25,26,27],"Design and implement REST and gRPC services with Spring Boot, Micronaut, or Quarkus","Own microservices architecture, DDD boundaries, and event-driven messaging with Kafka or Pulsar","Build data ingestion and transformation pipelines for ML training sets and evaluation signals","Integrate RLHF services to capture human feedback; maintain telemetry for large language model evaluation","Support annotation guidelines compliance through workflow orchestration and audit trails","Optimize JVM performance, garbage collection, and latency for high availability SLAs","Automate CI\u002FCD with GitHub Actions, Jenkins, or GitLab CI; deploy on Kubernetes and service meshes","Apply security best practices: OAuth2, OpenID Connect, secrets management, and compliance logging",{"h2":29,"desc":30,"bullets":31},"Key Responsibilities","Responsibilities vary by level and employer type. Core tasks emphasize production readiness, observability, and AI-adjacent integration.",[32,33,34,35,36,37,38,39],"Ship resilient APIs and backend services handling millions of requests","Implement streaming and batch pipelines for training data quality and labeling metadata","Add instrumentation for prompt evaluation metrics, human-in-the-loop feedback, and model scorecards","Build content safety labeling services to detect policy violations and route reviews","Process named entity recognition outputs; manage schema versioning and dataset lineage","Collaborate with data scientists to align inference endpoints and experiment tracking","Create automated QA evaluation harnesses for regression and fairness tests","Contribute to SRE practices: tracing, metrics, and distributed log correlation",{"h2":41,"desc":42,"bullets":43},"Required Skills","Strong Java fundamentals and modern platform engineering practice are essential.",[44,45,46,47,48,49,50,51],"Java 17+ and JVM internals, concurrency, reactive programming","Spring Boot, Spring Cloud, or Quarkus; REST, gRPC, GraphQL","SQL and NoSQL: PostgreSQL, MySQL, MongoDB, Redis, Elastic","Messaging and streaming: Kafka, Pulsar, RabbitMQ","Cloud-native infrastructure: Docker, Kubernetes, Helm, Terraform","Observability: OpenTelemetry, Prometheus, Grafana, ELK\u002FEFK","Security: OAuth2\u002FOIDC, JWT, mTLS, secret rotation, least-privilege IAM","Testing: JUnit5, Testcontainers, WireMock, contract testing",{"h2":53,"desc":54,"bullets":55},"Preferred Experience","Real-world delivery experience in AI\u002FML-centric environments helps candidates stand out.",[56,57,58,59,60,61,62,63],"ML-adjacent backend integration for RLHF pipelines and feedback aggregation","Data labeling workflow orchestration and annotation guidelines compliance","Model performance improvement through evaluation telemetry and A\u002FB testing","Large language model evaluation dashboards and automated score computation","NLP pipelines (NER, text classification) and feature store integrations","Computer vision annotation services and content safety moderation tooling","Event-driven architecture and CQRS in domain-heavy systems","High-throughput and low-latency JVM tuning for production workloads",{"h2":65,"desc":66,"bullets":67},"Domains and Project Types","Roles span classic enterprise backends and modern AI products.",[68,69,70,71,72,73,74],"NLP services for classification, summarization, and named entity recognition","Computer vision annotation and dataset management portals","Content safety labeling and trust & safety workflow engines","LLM training pipelines, RLHF feedback collection, and model evaluation services","FinTech, HealthTech, and GovTech microservices with compliance requirements","E-commerce search, personalization, and recommendation engines","Developer platforms: API gateways, service meshes, and internal developer portals",{"h2":76,"desc":77,"bullets":78},"Work Types and Search Modifiers","Explore roles that match your availability and seniority on Rex.zone.",[79,80,81,82,83],"Remote, contract, freelance, and full-time openings","Entry-level, mid-level, senior, staff, and principal roles","On-site and hybrid options across global hubs","Short-term consulting for platform migrations and JVM performance audits","Long-term product engineering in AI labs and tech startups",{"h2":85,"desc":86,"bullets":87},"Employer Types","Find teams aligned to your career goals.",[88,89,90,91,92],"AI labs building LLM training and evaluation infrastructure","Tech startups shipping microservices at rapid iteration cycles","BPOs and annotation vendors running large data labeling programs","Enterprise platforms modernizing legacy Java stacks to cloud-native","Research organizations and public sector innovation groups",{"h2":94,"desc":95,"bullets":96},"Tech Stack and Tools","Common stacks that appear across java software engineering jobs.",[97,98,99,100,101,102,103,104],"Languages: Java, Kotlin; build: Gradle, Maven","Frameworks: Spring Boot, Spring Cloud, Quarkus, Micronaut","Databases: PostgreSQL, MySQL, MariaDB, Cassandra, Redis","Messaging: Kafka, Pulsar, RabbitMQ; streaming with Flink or Spark","Cloud: AWS, GCP, Azure; infra as code with Terraform or Pulumi","Containers: Docker, Kubernetes, Helm, Argo CD","Auth and security: Keycloak, Okta, Vault; policy-as-code with OPA","CI\u002FCD: GitHub Actions, GitLab CI, Jenkins; quality gates with SonarQube",{"h2":106,"desc":107,"bullets":108},"Career Paths","Progress across responsibility and impact levels.",[109,110,111,112,113],"Entry-level: implement features, write tests, learn observability and CI\u002FCD","Mid-level: own services, contribute to architecture, improve performance","Senior: lead projects, define DDD boundaries, mentor engineers","Staff\u002FPrincipal: drive platform strategy, reliability, and cross-org standards","Manager\u002FEM: build teams, manage delivery, align product and technical roadmaps",{"h2":115,"desc":116,"bullets":117},"Compensation and Benefits","Transparent ranges are posted per employer; typical bands vary by location.",[118,119,120,121,122],"Entry-level: $70,000–$110,000 base or equivalent global bands","Mid-level: $110,000–$150,000 base; bonus and equity available","Senior: $150,000–$210,000 base; stock options and performance bonus","Contract rates: $50–$140\u002Fhr depending on scope, domain, and region","Benefits: remote stipend, learning budget, wellness, flexible hours",{"h2":124,"desc":125,"bullets":126},"Application Process","Rex.zone streamlines discovery and application.",[127,128,129,130,131,132],"Search java software engineering jobs and filter by remote, contract, or full-time","Review role scope, tech stack, and AI workflow integrations","Submit a simplified profile or upload CV and GitHub links","Complete technical assessment or share portfolio projects","Interview loops: system design, code tests, and culture fit","Receive fast feedback and standardized compensation summaries",{"h2":134,"desc":135,"bullets":136},"Why Rex.zone","A navigational hub built for developer careers and AI-aware backends.",[137,138,139,140,141],"High-signal job content curated for JVM and microservices roles","Unified discovery across AI labs, startups, BPOs, and annotation vendors","Deep filters for domain, seniority, salary, and time zone","Guides on RLHF, model evaluation, and data labeling workflows","Trusted employer reviews and transparent application tracking",{"h2":143,"desc":144,"bullets":145},"AI\u002FML Training Workflow Connections","Modern roles extend beyond traditional backend to ML-integrated platforms.",[146,147,148,149,150,151],"RLHF feedback loops integrated into microservices with reliable audit logs","Data labeling pipelines feeding curated datasets with lineage and versioning","Prompt evaluation services collecting human and automated metrics","Annotation guidelines compliance through workflow state machines","Model performance improvement tracked via telemetry and QA evaluation harnesses","Large language model evaluation dashboards using scoring schemas and cohorts",[153,165,177,188],{"title":154,"work_type":155,"employer_type":158,"location":159,"compensation":160,"highlights":161},"Senior Java Engineer — Spring Boot, Kafka, RLHF Integrations",[156,157],"remote","full-time","AI lab","Global, UTC±3 to UTC±8","USD $160,000–$200,000 + equity",[162,163,164],"Own microservices ingesting human feedback for model evaluation","Optimize JVM performance and backpressure handling for streaming pipelines","Collaborate with data science on evaluation metrics and dashboards",{"title":166,"work_type":167,"employer_type":170,"location":171,"compensation":172,"highlights":173},"Java Backend Developer — Content Safety Labeling Platform",[168,169],"hybrid","contract","Tech startup","US or EU hubs","$85–$120\u002Fhr",[174,175,176],"Build moderation APIs and reviewer workflow engines","Implement policy rules, audit trails, and privacy controls","Scale labeling throughput while maintaining annotation guidelines compliance",{"title":178,"work_type":179,"employer_type":181,"location":182,"compensation":183,"highlights":184},"Entry-Level Java Engineer — Data Labeling Tools",[156,180],"entry-level","Annotation vendor","EMEA and APAC","USD $70,000–$95,000",[185,186,187],"Develop features in labeling dashboards and task routing services","Write tests and observability probes for training data quality","Learn Spring Boot, Postgres, and CI\u002FCD pipelines",{"title":189,"work_type":190,"employer_type":191,"location":192,"compensation":193,"highlights":194},"Staff JVM Engineer — Distributed Systems, DDD",[156,157],"Enterprise platform","Americas","USD $190,000–$230,000 + bonus",[195,196,197],"Lead event-driven architecture, service boundaries, and reliability strategies","Guide platform migrations to Kubernetes and service mesh","Define platform-wide standards for tracing, security, and testing",{"primary_keyword":4,"secondary_keywords":199,"long_tail_keywords":227,"platform":243},[200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226],"Spring Boot jobs","JVM performance tuning","microservices architecture","distributed systems","Kubernetes Java developer","REST API development","Kafka streaming","Quarkus vs Spring","OpenTelemetry tracing","DevOps for Java","cloud-native Java","contract Java developer","freelance Java engineer","entry-level Java jobs","senior Java roles","AI backend engineer","LLM training pipelines","RLHF integration","data labeling platform","prompt evaluation tools","content safety labeling","named entity recognition","computer vision annotation","QA evaluation automation","model performance improvement","large language model evaluation","annotation guidelines compliance",[228,229,230,231,232,233,234,235,236,237,238,239,240,241,242],"best remote java software engineering jobs","top Spring Boot microservices roles","complete guide to JVM optimization","how to become a Java backend developer","Java engineer roles in AI labs","Java developer jobs for NLP pipelines","Java positions in content safety teams","contract Java roles with Kubernetes","freelance Java microservices expert","entry-level Java developer on Rex.zone","senior Java engineer salary bands","Spring Boot vs Quarkus performance","Kafka event-driven architecture jobs","Java roles in data labeling vendors","Rex.zone java software engineering jobs","Rex.zone",{"title":245,"content":246},"Frequently Asked Questions",[247,250,253,256,259,262],{"Q":248,"A":249},"What counts as java software engineering jobs on Rex.zone?","Roles involving JVM-based backend development, microservices, APIs, data pipelines, and platform engineering with Java or Kotlin. Many listings connect to AI workflows like RLHF collection, model evaluation telemetry, data labeling integrations, NER pipelines, and content safety labeling services.",{"Q":251,"A":252},"Are remote and contract options available?","Yes. You can filter by remote, contract, freelance, full-time, entry-level, and senior. Rex.zone surfaces employer types including AI labs, tech startups, enterprises, BPOs, and annotation vendors.",{"Q":254,"A":255},"Which stacks are most in demand?","Spring Boot, Spring Cloud, Kafka, PostgreSQL, Redis, Docker, Kubernetes, Terraform, OpenTelemetry, and OAuth2\u002FOIDC are common. Quarkus, Micronaut, and Kotlin also appear in performance-focused or greenfield services.",{"Q":257,"A":258},"How do these roles intersect with AI\u002FML training?","Java engineers build the infrastructure behind training data quality pipelines, prompt evaluation services, RLHF feedback loops, annotation guidelines compliance tooling, and large language model evaluation dashboards.",{"Q":260,"A":261},"What tips help applicants stand out?","Show production examples of resilient microservices, observability tooling, JVM tuning, and experience with ML-integrated backends. Highlight contributions to QA evaluation automation, data lineage, and security compliance.",{"Q":263,"A":264},"How do I apply on Rex.zone?","Create a profile, search java software engineering jobs, filter by modifiers and domains, review role details, and submit your application. Expect structured interview loops including code tests and system design."]