Principal Performance Engineer - Distributed Systems Tuning

Referral Board; Norway; On-site; NOK 950,000 - 1,502,000; Full time

Benefits offered by this job

Health coverage for you and family

Flexible locations & schedules

Generous vacation days

Donation matching

Volunteer hours

Parental leave 16 weeks

Job summary

Elastic is seeking a Principal Software Engineer to lead architectural and code-level performance initiatives for Elasticsearch. You will optimize distributed systems, profile bottlenecks, and drive AI-assisted benchmarking across diverse environments.

A strong background in Java internals, JVM memory, and performance tooling is essential. You will mentor engineers, partner with cross-functional teams, and influence feature design to ensure scalable, predictable performance in production and

Qualifications

• Deep knowledge of Java internals and JVM memory management.
• Proven experience profiling and optimizing distributed systems.
• Experience with benchmarking tools (JMH, Rally, Flamegraphs) and detecting regressions.
• Ability to automate benchmarking workflows using AI-assisted tooling.

Responsibilities

• Own performance engineering initiatives from architecture to production.
• Develop performance models and methodologies for complex distributed systems.
• Drive optimization strategies for performance, predictability, and scale.
• 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 teams to embed performance-first thinking in new features.

Skills

Java performance engineering

Profiling distributed systems

Distributed systems architecture

AI-assisted optimization

Cross-functional collaboration

Autonomous work

Tools

JMH

Rally

Flamegraphs

Profiling tools

Job description

Elastic is seeking a Principal Software Engineer to lead architectural and code-level performance initiatives for Elasticsearch. You will optimize distributed systems, profile bottlenecks, and drive AI-assisted benchmarking across diverse environments.

A strong background in Java internals, JVM memory, and performance tooling is essential. You will mentor engineers, partner with cross-functional teams, and influence feature design to ensure scalable, predictable performance in production and