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Principal 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
Principal Software Engineer role on the Elasticsearch Performance team, leading architectural and code-level performance engineering initiatives. Focus on optimizing and benchmarking distributed systems, collaborating across teams, and mentoring engineers to ensure Elasticsearch remains performant and scalable.
- Lead technical design, planning, and execution for major performance improvements
- Develop performance models and methodologies for distributed systems
- Drive optimization strategies for performance, predictability, and scalability
- Profile and analyze system behavior to identify bottlenecks
- Ensure robust performance benchmarks and regression detection
- Collaborate across teams to embed performance-first thinking
- Design and build AI-assisted optimization harnesses
- Mentor and coach other engineers
Key requirements
Must-have
- Deep knowledge of Java internals and JVM memory management
- Experience with concurrency models and writing high-performance, thread-safe, lock-free code
- Experience profiling and optimizing distributed systems
- Experience with benchmarking tools (e.g., flamegraphs, JMH, Rally)
- Understanding of distributed systems architecture
- Experience using AI or advanced tooling for optimization and benchmarking
- Ability to collaborate across teams and work autonomously
Nice-to-have
- Experience integrating high-performance native libraries (e.g., C++, Rust, SIMD-accelerated code) into Java applications
- Knowledge of modern storage engine performance or vector search optimizations
- Experience defining and managing Performance SLAs for distributed systems
- Experience working on internals of large-scale data stores or search engines
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 Principal Software Engineer to join the Elasticsearch Performance team. In this role, you will lead architectural and code-level performance engineering initiatives. Your goal is to drive the continuous optimization and predictability of Elasticsearch performance, partnering with area-specific teams to unlock the full potential of our software.
What You Will Be Doing
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Owning core performance engineering initiatives from architecture to production, focusing on the delivery of high-impact optimizations. Leading the technical design, plan, and execution for major architectural and code-level performance improvements.
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Developing foundational performance models and methodologies for complex, distributed systems.
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Driving 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 across the company to embed performance-first thinking into new features from the outset.
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Drive automation efforts by designing and building AI-assisted optimization harnesses that streamline profiling, hypothesis testing, and benchmarking.
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Mentoring and coaching other engineers, fostering a culture of technical excellence and performance-aware development.
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.,flamegraphs, 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 across functions and teams, acting as a force multiplier for performance engineering across the organization.
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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:
€104.800—€165.700 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
You will be assessed on your expertise in performance engineering for distributed systems, especially Elasticsearch, with deep Java/JVM knowledge, profiling and optimization skills, and the ability to lead architectural initiatives and mentor others.
- Performance optimization·High
- Distributed systems·High
- Java/JVM internals·High
- Profiling & benchmarking·High
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Java/JVM Internals
0–10 minFocus on concurrency, memory management, and lock-free programming relevant to high-performance systems.
Study Elasticsearch Performance Architecture
10–17 minUnderstand Elasticsearch's distributed architecture and typical performance challenges.
Refresh Profiling & Benchmarking Tools
17–24 minReview usage of flamegraphs, JMH, and Rally for identifying and resolving bottlenecks.
Prepare Leadership & Mentoring Examples
24–30 minRecall situations where you led optimization efforts or mentored engineers on performance topics.
Talking points
, 6 itemsJava and JVM Internals
Deep knowledge of Java internals and JVM memory management is explicitly required for optimizing Elasticsearch performance.
Distributed Systems Architecture
You must understand partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores.
Profiling and Benchmarking Tools
Experience with tools like flamegraphs, JMH, and Rally is essential for identifying and resolving performance bottlenecks.
Performance Optimization Strategies
You will lead high-impact optimizations, requiring expertise in algorithmic and hardware-aware improvements.
Automation and AI-Assisted Optimization
The role involves designing AI-assisted harnesses to automate profiling, hypothesis testing, and benchmarking.
Mentoring and Technical Leadership
You are expected to mentor engineers and drive a culture of performance-aware development.
What to research
, 3 itemsJava/JVM Performance and Concurrency
The role repeatedly emphasizes deep expertise in Java internals, concurrency, and memory management for high-performance, thread-safe code.
Distributed Systems Profiling and Optimization
You will be expected to lead performance engineering for distributed systems, including profiling, benchmarking, and addressing scaling challenges.
Technical Leadership and Mentoring
Mentoring and fostering a performance-aware culture is a core responsibility, so be ready to discuss your approach and impact.
Questions to ask
, 6 itemsHow does the Elasticsearch Performance team prioritize optimization initiatives?
Why ask this? Clarifies how your work will be directed and what drives priorities.
What are the most common performance bottlenecks currently faced in Elasticsearch?
Why ask this? Reveals where your expertise will have the most immediate impact.
How is collaboration structured between the performance team and other engineering teams?
Why ask this? Helps you understand cross-team dynamics and communication.
What tools and infrastructure are in place for automated benchmarking and regression detection?
Why ask this? Shows what resources you'll have for performance engineering.
What opportunities exist for mentoring or coaching within the team?
Why ask this? Clarifies expectations and opportunities for leadership.
How does Elastic support ongoing learning in performance engineering and distributed systems?
Why ask this? Indicates the company's commitment to professional development.
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