{"schemaVersion":"jobsearcher.job.v1","id":"ba7e3a43ad3f72afcb6e0e32","url":"https://jobsearcher.com/jobs/ba7e3a43ad3f72afcb6e0e32","canonicalUrl":"https://jobsearcher.com/jobs/ba7e3a43ad3f72afcb6e0e32","title":"Java Performance Engineer","description":"Title – Java Performance Engineer Location - St. Louis, MO(Onsite)Employment Type – Contract OnlyJob Description:-Define service-level objectives (SLOs), performance budgets, and latency/throughput targets across services.Architect and champion comprehensive distributed tracing strategies (Dynatrace, AWS X-Ray, etc.).Analyze application, platform, and cloud behaviour using deep-dive techniques such as heap dumps, thread dumps, flame graphs, GC logs, network traces, and storage I/O profiling.Review service and system architectures for performance risks (e.g., synchronous hops, excessive dependencies, misconfigured connection pools, poor cache placement).Conduct and lead root-cause analysis for performance incidents in production and pre-production environments.Develop capacity models and performance baselines for services running across cloud environments.Areas of ExpertiseApplication Layer: Spring Boot internals, JVM tuning, thread/heap management, concurrency debugging, GC optimizationContainer Runtime: PCF, Docker, container resource limits, CPU throttling, memory pressureOrchestrators: PCF, Kubernetes, ECS (autoscaling, pod health, scheduling issues)Networking: Service-to-service hops, TLS overhead, DNS, routing, load balancer configs (F5, Nginx, ALB/NLB), service mesh performanceStorage: Latency, IOPS constraints, distributed file system behaviourCaching & Middleware: Redis, Hazelcast, NATS, Kafka, RabbitMQ configuration and throughput tuningDatabases: Connection pool tuning, slow queries, indexing, replication lagCloud Layer: AWS compute/storage/network performance, regional latency, cross-cloud traffic patterns","company":"Hirein Solutions","rawCompany":"hirein solutions","city":"St Louis","state":"MO","isRemote":false,"isActive":false,"createdAt":"2026-09-23T07:55:14.622Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1211.00","title":"Computer Systems Analysts","slug":"computer-systems-analysts"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Java Performance Engineer","description":"Title – Java Performance Engineer Location - St. Louis, MO(Onsite)Employment Type – Contract OnlyJob Description:-Define service-level objectives (SLOs), performance budgets, and latency/throughput targets across services.Architect and champion comprehensive distributed tracing strategies (Dynatrace, AWS X-Ray, etc.).Analyze application, platform, and cloud behaviour using deep-dive techniques such as heap dumps, thread dumps, flame graphs, GC logs, network traces, and storage I/O profiling.Review service and system architectures for performance risks (e.g., synchronous hops, excessive dependencies, misconfigured connection pools, poor cache placement).Conduct and lead root-cause analysis for performance incidents in production and pre-production environments.Develop capacity models and performance baselines for services running across cloud environments.Areas of ExpertiseApplication Layer: Spring Boot internals, JVM tuning, thread/heap management, concurrency debugging, GC optimizationContainer Runtime: PCF, Docker, container resource limits, CPU throttling, memory pressureOrchestrators: PCF, Kubernetes, ECS (autoscaling, pod health, scheduling issues)Networking: Service-to-service hops, TLS overhead, DNS, routing, load balancer configs (F5, Nginx, ALB/NLB), service mesh performanceStorage: Latency, IOPS constraints, distributed file system behaviourCaching & Middleware: Redis, Hazelcast, NATS, Kafka, RabbitMQ configuration and throughput tuningDatabases: Connection pool tuning, slow queries, indexing, replication lagCloud Layer: AWS compute/storage/network performance, regional latency, cross-cloud traffic patterns","datePosted":"2026-09-23T07:55:14.622Z","dateModified":"2026-09-23T07:55:14.622Z","hiringOrganization":{"@type":"Organization","name":"Hirein Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"St Louis","addressRegion":"MO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ba7e3a43ad3f72afcb6e0e32"},"url":"https://jobsearcher.com/jobs/ba7e3a43ad3f72afcb6e0e32"}}