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Principal Software Engineer - Search Algorithms - Elasticsearch
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At a glance
- Employment type
- Full-time
- Location
- Ireland
- Workplace
- On-site
- Category
- Full-stack
Technologies & skills
Primary technologies
Other technical skills
What you'll be doing
Elastic is seeking a Principal Software Engineer for the Elasticsearch - Search team to enhance vector similarity search functionality. The role involves leading initiatives, contributing to new search features, and collaborating with a globally distributed team. Candidates should have experience with vector databases and strong Java skills.
- Lead initiatives to produce an industry-leading vector database offering.
- Contribute to Elasticsearch by building new search features and fixing bugs.
- Work with a globally distributed team focused on vector search capabilities.
- Be an expert on Elasticsearch's vector similarity implementation.
- Collaborate with community members on issues and pull requests.
- Write idiomatic modern Java.
Key requirements
Must-have
- Professional experience with vector similarity and vector databases.
- Strong skills in core Java and familiarity with data structures and concurrency.
- Ability to work autonomously and guide projects from beginning to end.
- Experience with data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
- Excellent verbal and written communication skills.
- Proven track record of using AI to accelerate development and optimize code.
Nice-to-have
- Experience building with Elasticsearch.
- Familiarity with open source projects and continuous integration.
- Experience designing and leading cross-functional initiatives.
Experience: Not specified
Role signals
- Technical focus
- Full-stack
- Hands-on vs management
- Mixed
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
We're looking for a Principal Software Engineer to join the Elasticsearch - Search team. This globally-distributed team of expert engineers focuses on delivering a robust and feature-rich search experience, including contributing to improving the search experience in Lucene. This is a principal software engineering role that focuses on enhancing the vector similarity search functionality within Elasticsearch, covering the design and implementation of new vector search features, enhancements to existing vector search functionality, and resolving bugs.
Our company is distributed by intention. We hire the best engineers we can find wherever they are, whoever they are. We collaborate across continents every day over email, GitHub, Zoom, and Slack. At our best, we write fast, scalable and intuitive software. We believe that the best way to do that is to empower individual engineers, code review every change, decide big things by consensus, and strive for incremental improvements.
What You Will Be Doing
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Lead initiatives within Elasticsearch to produce an industry-leading vector database offering, supplying unparalleled speed and relevance in search.
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Contribute to Elasticsearch full time, building new search features and fixing intriguing bugs, all while making the code easier to understand. Sometimes you'll need to invent a new algorithm or data structure. Or find one and implement it. Sometimes you'll need to get close to the operating system and hardware.
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Work with a globally distributed team of experienced engineers focused on the vector search capabilities of Elasticsearch.
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Be an expert on how Elasticsearch implements vector similarity in support of search relevance and everyone will turn to you when they have a question about this area. You'll improve this area based on your questions and your instincts.
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Work with community members from all over the world on issues and pull requests, sometimes triaging them and handing them off to other experts and sometimes handling them yourself.
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Write idiomatic modern Java -- Elasticsearch is 99.8% Java!
What You Bring Along
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Professional experience with vector similarity and vector databases, and you used HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.
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You have strong skills in core Java and are conversant in the standard library of data structures and concurrency constructs, as well as other features like lambdas.
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You work with a high level of autonomy, and are able to take on projects and guide them from beginning to end. This covers both technical design and working with other engineers to develop needed components.
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You're comfortable developing collaboratively. Giving and receiving feedback on code and approaches and APIs is hard! Bonus points if you've collaborated over the internet because that's harder. Double bonus points for asynchronous collaboration over the internet. That's even harder, but we do it anyway because it's the best way we know how to build software.
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You've used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way.
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You have excellent verbal and written communication skills. Like we said, collaborating on the internet is hard. We try to be respectful, empathetic, and trusting in all of our interactions. And we'd expect that from you too.
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You have a proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes.
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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 work autonomously and can drive decisions and results in a distributed team by leveraging asynchronous, direct, and transparent communication.
Bonus Points
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You've built things with Elasticsearch before.
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You've worked with open source projects and are familiar with different styles of source control workflow and continuous integration.
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Experience with data storage technology.
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You have experience designing, leading and owning cross-functional initiatives
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:
€102.700—€162.500 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 Principal Software Engineer role focuses on leading the design and implementation of advanced vector similarity search features in Elasticsearch, collaborating with a distributed team, and contributing to open source initiatives.
- Vector Search Expertise·High
- Java Mastery·High
- Distributed Collaboration·High
- Open Source Contribution·Medium
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Vector Search Algorithms and Elasticsearch Documentation
0–10 minStudy Elasticsearch's vector search features and refresh your knowledge of HNSW, IVF, and related algorithms.
Prepare Java and Concurrency Examples
10–17 minSelect and rehearse examples demonstrating your expertise in Java, focusing on performance, concurrency, and code quality.
Reflect on Distributed Team Experiences
17–22 minIdentify stories that showcase your ability to lead and collaborate in remote, asynchronous teams.
Research Open Source Contribution Practices
22–27 minReview best practices for code reviews, pull requests, and CI/CD in open source projects, especially on GitHub.
Draft Role-Specific Questions
27–30 minPrepare thoughtful questions about the team's technical challenges, collaboration style, and success metrics.
Talking points
, 6 itemsVector Similarity Search and Algorithms (e.g., HNSW, IVF)
You should be ready to discuss your hands-on experience designing, implementing, or optimizing vector search algorithms, as this is central to the role.
Core Java Skills and Concurrency
Demonstrating deep knowledge of Java, including data structures, concurrency, and idiomatic code, will show your technical fit for Elasticsearch's codebase.
Leading Technical Initiatives and Autonomy
Prepare examples where you independently led projects from design to delivery, as the role expects high autonomy and ownership.
Collaboration in Distributed, Asynchronous Teams
Showcase your ability to communicate and collaborate effectively across time zones and cultures, especially in open source or remote-first environments.
Experience with Data Storage Technologies
Be ready to discuss your practical experience with Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra, and how you leveraged them in search or data-intensive applications.
Using AI to Accelerate Development
Share concrete examples of how you have used AI tools or techniques to debug, optimize, or accelerate software development.
What to research
, 4 itemsElasticsearch Vector Search Capabilities
Review Elasticsearch's current vector search features, APIs, and recent enhancements, especially around similarity algorithms.
Modern Java Practices
Brush up on idiomatic Java, concurrency constructs, and best practices for large-scale, high-performance systems.
Distributed Team Collaboration
Prepare examples of working in distributed, asynchronous teams, including tools and communication strategies.
Open Source Contribution Workflows
Familiarize yourself with open source collaboration, code review, and continuous integration practices, especially on GitHub.
Questions to ask
, 6 itemsWhat are the current technical challenges or priorities for vector search within Elasticsearch?
Why ask this? To understand the team's focus and how your expertise can contribute.
How does the team approach consensus and decision-making in a globally distributed environment?
Why ask this? To gauge the collaboration style and your fit within the team.
What is the process for contributing new features or major changes to Elasticsearch?
Why ask this? To clarify expectations around technical ownership and open source workflows.
How does the team balance innovation in search algorithms with the need for stability and backward compatibility?
Why ask this? To understand the constraints and priorities in feature development.
What opportunities exist for cross-functional collaboration with other teams or the broader Elastic community?
Why ask this? To explore how you might engage beyond the immediate team.
How is success measured for this role and for the vector search initiatives?
Why ask this? To clarify performance expectations and impact.
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