We are seeking a highly skilled and experienced Performance Engineer to lead performance-focused development initiatives across large-scale distributed systems. The ideal candidate will drive performance optimization, scalability, and reliability across complex architectures, influencing system design decisions. NIFN2026 Performance Engineering & Optimization Identify, analyse, and resolve performance bottlenecks across application, middleware, and infrastructure layers. Conduct deep-dive analysis into CPU, memory, I/O, network, and latency issues. Drive performance tuning initiatives for high-throughput and low-latency systems. Establish performance benchmarks and define SLAs/SLOs for critical services. Debugging & Troubleshooting at Scale Lead root cause analysis for production performance issues and outages. Debug complex issues in distributed environments involving multiple services and dependencies. Analyse thread dumps, heap dumps, GC logs, and profiling data to diagnose issues. Work closely with DevOps and Arch teams for arriving at Scalable Solutions/Fix. System Design & Architecture Provide design recommendations with a strong focus on Performance, Scalability and Resilience. Evaluate trade-offs in distributed system design (e.g., consistency vs availability, throughput vs latency). Influence architecture decisions for microservices, event-driven systems, and data pipelines. Ensure systems are designed to handle large-scale workloads efficiently. Benchmarking & Capacity Planning Design and execute performance tests (load, stress, endurance, spike testing). Build benchmarking frameworks for new and existing features. Perform capacity planning and forecasting for infrastructure and application growth. Validate system behaviour under peak and failure scenarios. Feature Development at Scale Contribute to development of new features with performance considerations from design to implementation. Ensure efficient resource utilization and minimal performance overhead. Optimize APIs, data models, and processing pipelines for scale. Required Skills & Qualifications Graduate or Postgraduate in Engineering with 8 to 14 years of strong experience in Java performance tuning and JVM internals. Solid understanding of distributed systems and microservices architecture. Hands-on experience with containerized environments (Kubernetes). Deep knowledge of messaging systems (Kafka) and data stores. Experience in performance testing, benchmarking, and capacity planning. Strong debugging and analytical skills in complex production environments. Proven ability to lead teams and drive technical initiatives. Preferred Qualifications Experience with large-scale telecom or network management systems. Exposure to real-time data processing and observability platforms. Familiarity with cloud-native architectures and CI/CD pipelines. Knowledge of system-level tuning (Linux kernel, networking, Muti Threading etc…). Core Technologies Languages: Java (primary), Bash, Python (supporting) Frameworks & Platforms: Karaf (OSGi-based runtime) Kubernetes, Helm Apache Kafka (event streaming) OpenSearch/Elasticsearch (search & analytics) OpenTSDB (time-series data) Valkey /Redis (in-memory data store) MariaDB (relational database) Keycloak (Single-SignOn/authentication and identity systems) Performance Analysis & Debugging Tools (JVM & Application Profiling) jstack (thread dump analysis) jmap (heap dump and memory analysis) MAT (Memory Analyzer Tool) VisualVM Java Flight Recorder (JFR) Kubernetes Tools: kubectl, metrics-server, Prometheus, Grafana Async Profiler (CPU & allocation profiling) YourKit / JProfiler (advanced profiling) GC Logs Analyzer tools (GCViewer, GCeasy) Linux Tools: top, htop, vmstat, iostat, netstat, sar Network Debugging: tcpdump, Wireshark Load Testing Tools: JMeter Logging & Observability: OpenSearch, Kibana Key Competencies Problem-solving and analytical thinking Quantitative Thinking - What you can’t measure you can’t improve. Leadership and mentoring Performance-first mindset Strong communication and collaboration Ownership and accountability
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