We are looking for a Senior Performance Engineer who specializes in optimizing Java-based, containerized applications running in cloud environments. This role is critical in ensuring that our micro-services architecture operates with high efficiency, low latency, and optimal resource utilization at scale. You will be responsible for identifying, diagnosing, and resolving performance bottlenecks across Java, Spring Boot, Kubernetes, and distributed data stores.

REQUIREMENTS

• 8+ years of experience in performance engineering, specifically for Java-based, containerized applications.
• Deep expertise in JVM internals, memory management, and thread optimization.
• Hands-on experience with Spring Boot and its performance tuning.
• Proficiency in Kubernetes, including resource tuning, scaling strategies, and troubleshooting pod/container-level performance issues.
• Strong database performance skills across SQL, NoSQL, and in-memory caching solutions.
• Experience with profiling, monitoring, and observability tools for root-cause analysis.
• Knowledge of asynchronous programming and reactive patterns to enhance system responsiveness.
• Strong background in message-driven architectures and event stream processing.
• Experience with CI/CD pipelines to integrate performance testing into the development lifecycle

• End-to-End Performance Optimization: Analyze and enhance the performance of Java microservices deployed in Kubernetes environments to ensure scalability, reliability, and minimal resource consumption.
• Container & Orchestration Performance: Tune Dockerized applications for efficient resource utilization, leveraging Kubernetes features (e.g., Horizontal/Vertical Pod Autoscaling, Cluster Autoscaler, CPU/Memory limits, KEDA).
• Java Performance Tuning: Optimize JVM performance, garbage collection (GC) tuning, thread management, and memory allocation to minimize latency and maximize throughput.
• Spring Boot Optimization: Profile and fine-tune Spring Boot applications, including database connections, thread pools, reactive streams, and caching strategies.
• Database Performance Engineering: Improve query execution times and indexing strategies across relational (PostgreSQL, MySQL, AWS RDS Aurora), NoSQL (Cassandra, DynamoDB), and in-memory databases (Redis, Memcached).
• Observability & Profiling: Utilize tools like JVM Flight Recorder, JFR, JVisualVM, YourKit, JProfiler, and distributed tracing solutions (Jaeger, Zipkin, OpenTelemetry) to diagnose slowdowns.
• Load & Stress Testing: Design and execute load, stress, and chaos engineering tests using tools like JMeter, k6 to simulate high-traffic scenarios.
• Message-Driven Performance: Optimize performance in event-driven architectures using Kafka or RabbitMQ.
• Cloud-Native Performance Optimization: Work with AWS and GCP to optimize auto-scaling, networking, and service mesh performance (Istio, Linkerd).
• Automation & Continuous Performance Testing: Develop CI/CD-integrated performance benchmarking suites to proactively identify performance regressions.