Overview

As Principal Software Engineer on the Elasticsearch Performance team, you drive core performance improvements from architecture to production to ensure fast, scalable search and AI retrieval. You will lead design and execution of major optimizations, develop performance models for complex distributed systems, and embed performance as a first-class consideration in new features. You'll benchmark, profile, and optimize across logging, metrics, vector search, and ES|QL, while mentoring engineers and advancing AI-assisted optimization.

This role offers impact at scale, shaping how Elasticsearch performs in diverse environments.

Compensaciones / Ventajas Competitive pay

Health coverage for you and family

Flexible locations and schedules

Generous vacation days

Donation matching up to 2000

Volunteer hours (up to 40 per year)

Responsabilidades

Own core performance initiatives end-to-end, from architecture to production deployment

Lead technical design and execution for major architectural and code-level performance improvements

Develop foundational performance models and methodologies for distributed systems

Drive optimization strategies for performance, predictability, and scalability of Elasticsearch

Profile and analyze system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL





Ensure robust performance benchmarks and regression detection for stateful and serverless architectures

Collaborate across the company to embed performance-first thinking in new features

Design and build AI-assisted optimization harnesses to streamline profiling, hypothesis testing, and benchmarking

Mentor and coach engineers to foster technical excellence and performance-aware development

Requisitos principales Deep knowledge of Java internals and JVM memory management

Strong understanding of concurrency models; ability to write high-performance, thread-safe, lock-free code

Experience with large open-source and enterprise codebases

Proven profiling and optimization experience for distributed systems

Familiarity with benchmarking tools (flamegraphs, JMH, Rally) and identifying performance regressions

Solid grasp of distributed systems architecture (partition tolerance, cluster state propagation, scaling challenges)

Proven track record using AI or advanced tooling to accelerate optimization and automate benchmarking

Ability to collaborate across functions and teams and work autonomously in distributed settings

Cross-functional collaboration

Mentoring and coaching

Autonomous decision-making and clear communication

Java, JVM internals, memory management

Concurrency models, thread-safety, lock-free design

Profiling and benchmarking (flamegraphs, JMH, Rally)

📌 Principal Software Engineer - Performance Tuning - Elasticsearch (San Sebastián)
🏢 Elastic
📍 San Sebastián