Principal Software Engineer (Performance Tuning, Elasticsearch)

Join the Elasticsearch Performance team as a Principal Software Engineer. In this role, you will lead performance engineering initiatives, drive optimization strategies, and collaborate across the company to embed performance-first thinking into new features. You will also mentor and coach other engineers, fostering a culture of technical excellence and performance-aware development.

• Lead architectural and code-level performance engineering initiatives for Elasticsearch, focusing on high-impact optimizations.
• Develop foundational performance models and methodologies for complex, distributed systems, driving optimization strategies.
• Collaborate across the company to embed performance-first thinking into new features, and mentor other engineers in performance-aware development.
• You have a proven track record of using AI or advanced tooling to accelerate optimization, debug complex performance issues, and automate benchmarking workflows
• You can work autonomously, drive decisions and result in a distributed team by leveraging asynchronous, direct, and transparent communication
• You have deep knowledge of Java internals and JVM memory management. You understand how concurrency models work. You can write code that is high-performance, thread-safe, and lock-free. This experience includes working with large open-source and enterprise codebases
• You have a solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores
• You possess the ability to collaborate across functions and teams and seamlessly transition between different projects, codebases, or teams based on business priorities
• You possess the ability to collaborate across functions and teams, acting as a force multiplier for performance engineering across the organization
• You have proven experience in profiling and optimizing distributed systems. This includes deep experience with benchmarking tools (e.g., flamegraphs, JMH, Rally), identifying performance regressions, and implementing algorithmic or hardware-aware optimizations
• Experience integrating high-performance native libraries (e.g., C++, Rust, SIMD-accelerated code) into Java applications
• Deep knowledge of modern storage engine performance, index modes, or vector search optimizations
• Experience defining and managing Performance SLAs and success criteria for distributed systems
• Experience working on the internals of a large-scale data store or search engine
• Experience working on the internals of a data store or search engine