Principal Software Engineer, Performance Tuning, Elasticsearch

Elastic

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Posted
24 days ago
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Confirmed live yesterday

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Similar $201k
$130k most similar roles pay here $260k

This listing doesn't post a salary. Most similar roles pay $172,350–$230,625.

Based on 240 similar postings.

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About Elastic

Elastic is the company behind Elasticsearch and the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). It sells search, observability, and security products built on that search engine, primarily through its Elastic Cloud managed service.

Elastic currently has 240 open roles on FindRole.

Listed pay typically runs $133,100–$210,600 across 91 roles with salary data.

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TL;DR · Principal Software Engineer, Performance Tuning, Elasticsearch

As a Principal Software Engineer - Performance Tuning - Elasticsearch, you will join the Elasticsearch Performance team to lead architectural and code-level performance engineering initiatives. You will be responsible for driving optimization strategies, developing foundational performance models for complex distributed systems, and identifying bottlenecks in logging, metrics, vector search, and ES|QL. Your daily work involves profiling system behavior, ensuring robust benchmarks for stateful and stateless architectures, and building AI-assisted optimization harnesses to automate benchmarking workflows. The role requires deep expertise in Java internals, JVM memory management, concurrency models, and high-performance, thread-safe code. You will utilize tools like flamegraphs, JMH, and Rally while leveraging advanced tooling to solve scalability challenges in large-scale data stores. This position focuses on ensuring the performance and predictability of search, observability, and AI retrieval systems for enterprise-scale infrastructure.

What does a Software Engineer earn?

Median $197500 from 2196 postings across 133 companies.

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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

  • Deep knowledge of Java internals, JVM memory management, and concurrency models.
  • Ability to write high-performance, thread-safe, and lock-free code in large open-source or enterprise codebases.
  • Proven experience profiling and optimizing distributed systems using tools like flamegraphs, JMH, and Rally.
  • Solid understanding of distributed systems architecture, including partition tolerance and cluster state propagation.
  • Proven track record of using AI or advanced tooling to automate benchmarking and debug complex performance issues.
  • Ability to work autonomously in a distributed team using asynchronous and transparent communication.
  • Experience integrating high-performance native libraries like C++, Rust, or SIMD-accelerated code (preferred).
  • Knowledge of storage engine performance, index modes, vector search optimizations, or managing Performance SLAs (preferred).

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