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Senior Software Engineer - Performance Tuning - Elasticsearch
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At a glance
- Employment type
- Full-time
- Location
- Ireland
- Workplace
- On-site
- Category
- Full-stack
Technologies & skills
What you'll be doing
Senior Software Engineer role on the Elasticsearch Performance team, focused on optimizing and benchmarking Elasticsearch for scalability and predictability. Responsibilities include profiling, technical analysis, and collaborating with teams to deliver high-quality performance improvements in distributed systems.
- Contribute to core performance engineering initiatives from development to production
- Execute technical designs and plans for architectural and code-level performance improvements
- Implement foundational performance models and methodologies for complex, distributed systems
- Support optimization strategies for performant, predictable, and scalable 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 stateless architectures
- Collaborate with peers to apply performance-focused development practices into new features
- Contribute to automation efforts by building AI-assisted optimization harnesses
Key requirements
Must-have
- Deep knowledge of Java internals and JVM memory management
- Understanding of concurrency models and ability to write high-performance, thread-safe, lock-free code
- Experience with large open-source and enterprise codebases
- Proven experience in profiling and optimizing distributed systems
- Experience with benchmarking tools (e.g., JMH, Rally)
- Ability to identify performance regressions and implement optimizations
- Solid comprehension of distributed systems architecture
- Track record of using AI or advanced tooling for optimization and benchmarking automation
Nice-to-have
- Experience integrating high-performance native libraries (e.g., C++, Rust, SIMD-accelerated code) into Java applications
- Deep knowledge of modern storage engine performance, index modes, or vector search optimizations
- Experience defining and managing Performance SLAs and success criteria for distributed systems
- Experience working on the internals of a large-scale data store or search engine
Role signals
- Technical focus
- performance engineering, distributed systems, optimization
- Leadership
- Mentoring
- Architecture / system design
- Indicated in the listing
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
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 precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.
What is The Role
Elasticsearch powers search, observability, and AI retrieval (RAG) for the world's largest organizations. We are seeking a Senior Software Engineer to join the Elasticsearch Performance team. In this role, you will contribute to performance engineering initiatives through high-quality code and technical analysis. Your goal is to help improve the optimization and predictability of Elasticsearch performance, collaborating with area-specific teams to enhance our software.
What You Will Be Doing
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Contributing to core performance engineering initiatives from development to production, focusing on the delivery of impactful optimizations. Executing technical designs and plans for architectural and code-level performance improvements.
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Implementing foundational performance models and methodologies for complex, distributed systems.
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Supporting optimization strategies to ensure Elasticsearch remains performant, predictable, and scalable in diverse environments.
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Profiling and analyzing system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL.
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Ensuring robust performance benchmarks and regression detection for both stateful and stateless (Serverless) architectures.
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Collaborating with peers across the team to apply performance-focused development practices into new features.
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Contributing to automation efforts by building AI-assisted optimization harnesses that streamline profiling, hypothesis testing, and benchmarking.
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Providing technical guidance and peer reviews to other engineers, fostering a culture of technical excellence.
What You Bring
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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.
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You have proven experience in profiling and optimizing distributed systems. This includes deep experience with benchmarking tools (e.g., JMH, Rally), identifying performance regressions, and implementing algorithmic or hardware-aware optimizations.
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You have a solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores.
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You have a proven track record of using AI or advanced tooling to accelerate optimization, debug complex performance issues, and automate benchmarking workflows.
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You possess the ability to collaborate effectively within a team environment, contributing to the success of performance engineering goals.
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You possess the ability to collaborate across functions and teams and seamlessly transition between different projects, codebases, or teams based on business priorities
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You can work autonomously, drive decisions, and result in a distributed team by leveraging asynchronous, direct, and transparent communication.
Bonus Points
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Experience integrating high-performance native libraries (e.g., C++, Rust, SIMD-accelerated code) into Java applications.
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Deep knowledge of modern storage engine performance, index modes, or vector search optimizations.
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Experience defining and managing Performance SLAs and success criteria for distributed systems.
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Experience working on the internals of a large-scale data store or search engine.
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Experience working on the internals of a data store or search engine.
Compensation for this role is in the form of base salary. This role does not have a variable compensation component.
At Elastic, our compensation philosophy aims to provide fair, competitive and transparent remuneration. Salary ranges are established based on a combination of external market benchmarks, internal pay equity considerations, and the responsibilities and complexity associated with each role. This approach helps ensure consistency across comparable roles while remaining competitive within the relevant labour markets.
The final compensation offered within the applicable range will be determined based on several objective factors, including relevant professional experience, level of skills and expertise, alignment with the role requirements, and the overall scope and complexity of the position.
The typical starting salary range for this role is:
€87.300—€138.100 EUR
Additional Information - We Take Care of Our People
As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.
We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.
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Competitive pay based on the work you do here and not your previous salary
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Health coverage for you and your family in many locations
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Ability to craft your calendar with flexible locations and schedules for many roles
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Generous number of vacation days each year
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Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
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Up to 40 hours each year to use toward volunteer projects you love
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Embracing parenthood with minimum of 16 weeks of parental leave
Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.
We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email candidate_accessibility@elastic.co. We will reply to your request within 24 business hours of submission.
Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster)
Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries’ export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.
Please see here for our Privacy Statement.
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
Based on this listing, the Senior Software Engineer - Performance Tuning - Elasticsearch role centers on driving performance engineering initiatives, optimizing distributed systems, and collaborating on architectural improvements for Elasticsearch. The position emphasizes deep technical expertise in Java, distributed systems, and benchmarking, with a strong focus on hands-on optimization and automation.
- Java and JVM expertise·Medium
- Distributed systems performance·High
- Benchmarking and automation·High
- Collaboration and technical leadership·High
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Java Performance and Concurrency Concepts
0–8 minRefresh your knowledge of JVM internals, memory management, and advanced concurrency patterns relevant to high-performance systems.
Study Distributed Systems and Elasticsearch Architecture
8–15 minFocus on partitioning, cluster state management, and scaling in Elasticsearch or similar distributed data stores.
Practice Profiling and Benchmarking
15–22 minSet up sample projects to use tools like JMH or Rally, and analyze performance bottlenecks.
Prepare Examples of Performance Optimization and Collaboration
22–27 minSelect 2-3 impactful stories from your experience that demonstrate technical depth and teamwork.
Draft Role-Specific Questions
27–30 minWrite down thoughtful questions about team processes, technical challenges, and success metrics to ask during the interview.
Talking points
, 5 itemsJava Internals and JVM Memory Management
Demonstrate your expertise in writing high-performance, thread-safe, and lock-free code, and your ability to optimize Java applications at the JVM level.
Distributed Systems Architecture
Showcase your understanding of partition tolerance, cluster state propagation, and scaling challenges relevant to Elasticsearch and similar large-scale data stores.
Profiling, Benchmarking, and Regression Detection
Provide examples of using tools like JMH or Rally to identify bottlenecks, measure performance, and prevent regressions in complex systems.
AI-Assisted Optimization and Automation
Highlight your experience leveraging AI or advanced tooling to accelerate optimization, automate benchmarking, and debug performance issues.
Collaboration and Technical Guidance
Prepare to discuss how you have contributed to team success, mentored peers, and fostered a culture of technical excellence.
What to research
, 4 itemsJava Concurrency and JVM Tuning
Review advanced Java concurrency patterns, JVM memory management, and lock-free programming techniques.
Distributed Systems Performance
Study Elasticsearch architecture, focusing on partition tolerance, cluster state, and scaling challenges.
Benchmarking Tools and Methodologies
Familiarize yourself with JMH, Rally, and other relevant profiling and benchmarking tools.
AI-Assisted Optimization Workflows
Explore how AI and automation can be used to streamline profiling, hypothesis testing, and benchmarking.
Questions to ask
, 6 itemsHow does the performance engineering team prioritize optimization initiatives across different Elasticsearch features?
Why ask this? Clarifies how work is scoped and prioritized, helping you understand team focus and expectations.
What are the most common performance challenges currently faced in Elasticsearch, especially with new features like vector search or ES|QL?
Why ask this? Gives insight into real-world technical challenges and where your expertise could have the most impact.
How is benchmarking and regression detection integrated into the development and release cycle?
Why ask this? Helps you understand the maturity of performance testing and automation in the workflow.
What opportunities exist for contributing to open-source or cross-team performance initiatives?
Why ask this? Reveals the scope for collaboration and influence beyond your immediate team.
How does the team leverage AI or advanced tooling in day-to-day performance engineering tasks?
Why ask this? Clarifies the extent of innovation and automation in the team's approach.
What does success look like for this role in the first 6-12 months?
Why ask this? Sets clear expectations for impact and performance in the role.
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