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.
• Build AI-assisted optimization harnesses to automate profiling, hypothesis testing, and benchmarking.
• Mentor and coach other engineers to foster a culture of technical excellence.

What we're looking for

• Deep knowledge of Java internals, JVM memory management, and concurrency models to write high-performance, thread-safe, and lock-free code.
• Proven experience in profiling and optimizing distributed systems using tools like flamegraphs, JMH, and Rally.
• Solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges.
• Proven track record of using AI or advanced tooling to accelerate optimization, debug performance issues, and automate benchmarking workflows.
• Ability to work autonomously in a distributed team while communicating across functions and collaborating on diverse projects.
• Experience integrating high-performance native libraries like C++, Rust, or SIMD-accelerated code (preferred).
• Deep knowledge of modern storage engine performance, index modes, or vector search optimizations (preferred).
• Experience defining Performance SLAs and working on the internals of large-scale data stores or search engines (preferred).