The opportunity
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the…
What you'll do
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.
What they're looking for
- Drive 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.
- 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 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.
