Principal Software Engineer - Performance Tuning - Elasticsearch

What is The Role

Elasticsearch powers search, observability, and AI retrieval (RAG) for the world's largest organizations. We are seeking a Principal Software Engineer to join the Elasticsearch Performance team. In this role, you will lead architectural and code-level performance engineering initiatives. Your goal is to drive the continuous optimization and predictability of Elasticsearch performance, partnering with area-specific teams to unlock the full potential of our software.

What You Will Be Doing

• Owning core performance engineering initiatives from architecture to production, focusing on the delivery of high-impact optimizations. Leading the technical design, plan, and execution for major architectural and code-level performance improvements.
• Developing foundational performance models and methodologies for complex, distributed systems.
• Driving optimization strategies to ensure Elasticsearch remains performant, predictable, and scalable in diverse environments.
• Profiling and analyzing system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL.
• Ensuring robust performance benchmarks and regression detection for both stateful and stateless (Serverless) architectures.
• Collaborating across the company to embed performance-first thinking into new features from the outset.
• Driving automation efforts by designing and building AI-assisted optimization harnesses that streamline profiling, hypothesis testing, and benchmarking.
• Mentoring and coaching other engineers, fostering a culture of technical excellence and performance-aware development.

What You Bring

• Deep knowledge of Java internals and JVM memory management; deep understanding of concurrency models and the ability to write high-performance, thread-safe, and lock-free code within large codebases.
• Proven experience in profiling and optimizing distributed systems, including benchmarking tools (e.g., flamegraphs, JMH, Rally), identifying regressions, and implementing algorithmic or hardware-aware optimizations.
• Solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores.
• Proven track record of using AI or advanced tooling to accelerate optimization, debug complex performance issues, and automate benchmarking workflows.
• Ability to collaborate cross-functionally and act as a force multiplier for performance engineering.
• Ability to transition seamlessly between different projects, codebases, or teams based on business priorities.
• Ability to work autonomously and drive decisions in a distributed team leveraging asynchronous, direct, and transparent communication.

Bonus Points

• 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.