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AI Summary
About B2Spin
We are B2Spin, and we are dedicated to delivering the best Free-to-Play Social Casino and gaming experiences by creating captivating, engaging, and unique products that are accessible to everyone. We have built a team of talented professionals from all over the globe, who are working to continually improve the experiences of our players. We are not looking to just be part of the industry, but to revolutionize it.
AI-Driven Engineering Culture
We are actively building an AI-driven engineering organization with a clear and deliberate stance: artificial intelligence is a core part of how we build and deliver software — not an experiment, not a trend, and not an optional add-on.
AI is embedded into our engineering workflows, from system design and prototyping to refactoring, testing, and code review. We expect engineers to be fully comfortable working in AI-driven environments and to treat AI as a primary productivity multiplier. Strong engineering judgment, architectural ownership, and accountability remain essential—AI amplifies our engineers, it doesn’t replace responsibility for technical decisions.
What you will be doing
• 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
What we are looking for
• 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
Nice to have:
• 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.
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