Principal Software Engineer, Performance Tuning, Elasticsearch

What you'll do

• Lead architectural and code-level performance engineering initiatives from design to production.
• Develop foundational performance models and methodologies for complex, distributed systems.
• Drive optimization strategies to ensure Elasticsearch remains performant, predictable, and scalable.
• Profile and analyze system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL.
• Establish robust performance benchmarks and regression detection for stateful and stateless architectures.
• Design and build AI-assisted optimization harnesses to automate profiling and benchmarking workflows.
• Mentor and coach other engineers to foster a culture of technical excellence.

What we're looking for

• You must have deep knowledge of Java internals, JVM memory management, and concurrency models.
• You must be able to write high-performance, thread-safe, and lock-free code for large open-source or enterprise codebases.
• You must have proven experience profiling and optimizing distributed systems using tools like flamegraphs, JMH, and Rally.
• You must have a solid understanding of distributed systems architecture, including partition tolerance and cluster state propagation.
• You must have a track record of using AI or advanced tooling to automate benchmarking and debug complex performance issues.
• You must be able to work autonomously in a distributed team using asynchronous and transparent communication.
• Experience integrating high-performance native libraries like C++, Rust, or SIMD into Java applications (preferred).
• Experience with storage engine performance, vector search optimizations, or large-scale data store internals (preferred).