Principal Java Engineer - Distributed Systems (Serverless)

Neura Market; Ireland; Remote; EUR 105,000 - 166,000; Full time

Benefits offered by this job

Health coverage

Flexible locations

Generous vacation

Donation matching

Volunteer time

Parental leave

Job summary

Elastic is seeking a Principal Software Engineer for the Elasticsearch - Distributed Systems team. You will focus on scale, performance, and resilience in our Serverless offering, tackling deep distributed systems challenges across nodes in an Elasticsearch cluster.

You will design, build, and operate core components, ensure efficient indexing across machines, and drive performance under dynamic cluster conditions. Remote-friendly, global collaboration is expected.

Qualifications

• Deep background in distributed systems and consensus algorithms.
• Strong core Java skills and knowledge of data structures and concurrency.
• Proficiency in algorithms and large-scale distributed systems.
• Experience building and debugging multi-machine features with ownership.

Responsibilities

• Design, build, and operate core pieces of the next-gen Serverless Elasticsearch offering.
• Improve components for concurrent and consistent indexing across machines.
• Maintain cluster coordination to preserve performance as nodes join/leave.
• Push limits on shards, nodes, and petabytes managed by Elasticsearch.
• Investigate performance/concurrency issues and propose solutions.
• Support engineers with advanced problems and own end-to-end investigations.

Skills

Distributed systems

Java

Algorithms

Large-scale systems

Project ownership

Cross-team collaboration

AI acceleration

Tools

Netty

JDK

Lucene

Job description

Elastic is seeking a Principal Software Engineer for the Elasticsearch - Distributed Systems team. You will focus on scale, performance, and resilience in our Serverless offering, tackling deep distributed systems challenges across nodes in an Elasticsearch cluster.

You will design, build, and operate core components, ensure efficient indexing across machines, and drive performance under dynamic cluster conditions. Remote-friendly, global collaboration is expected.