b2spin - Staff Backend Engineer
Requirements
• Deep, low-level understanding of Java internals (JVM, GC behavior, memory management, concurrency/multithreading, and performance profiling) • Advanced knowledge of relational databases (PostgreSQL), including query optimization, indexing strategies, locking mechanisms, and connection pooling under heavy load and distributed systems architecture, specifically high-throughput event streaming with Kafka (partitioning, replication, consumer group rebalancing, and tuning). • Strong system design, troubleshooting and debugging capabilities • Comfortable and proactive in using AI coding assistants (GitHub Copilot, Claude Code, etc.) as productivity multipliers • Practical experience validating, refining, and taking ownership of AI-generated output • Upper-intermediate or higher level of English • Proven track record of building or maintaining shared libraries, SDKs, or internal tooling in a large-scale engineering organization. • Hands-on experience with APM tools and observability stacks (Prometheus, Grafana, ELK) with the ability to define meaningful SLOs/SLIs, custom metrics, and proactive alerts. • Main technologies: Java, Spring, Spring Boot, Ebean-ORM, Quartz, Maven, Resteasy, Flyway, PostgreSQL 15, HTTP/Websockets, Netty, K8S/Docker, GCP, Jenkins, ELK, Grafana.
Responsibilities
• Design, evolve, and maintain core libraries, framework extensions, and shared components used across all engineering teams • Take ownership of system performance, scalability, and high-load architecture, ensuring core services can handle massive throughput with low latency • Proactively monitor production behavior, investigate complex application/database performance bottlenecks, and introduce advanced metrics, dashboards, and alerting systems • Establish and advocate for best practices in concurrency, memory management, and resource utilization across the backend ecosystem • Collaborate with cross-functional teams including backend, web, mobile, QA, and product teams • Take ownership of specific functional areas within our large-scale architecture • Leverage AI tools and assistants as integral parts of your development workflow—from system design to code review • Contribute to maintaining high test coverage, predictable production behavior, and seamless scalability • Drive engineering excellence through modern practices and continuous improvement
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