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Senior Software Engineer - Vector Search - 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 Senior Software Engineer for the Elasticsearch - Search Relevance team. This role involves leading initiatives to enhance search capabilities, contributing to the development of new features, and collaborating with a globally distributed team. The ideal candidate will have experience with vector similarity techniques and a strong background in Java.
- Lead initiatives within Elasticsearch to produce an industry-leading search engine offering.
- Contribute to Elasticsearch full time, building new search features and fixing bugs.
- Work with a globally distributed team focused on vector search capabilities.
- Identify and drive improvements in search relevance.
- Collaborate with community members on issues and pull requests.
Key requirements
Must-have
- Experience with search or vector databases.
- Solid skills in core Java.
- Ability to work autonomously and guide projects from beginning to end.
- Experience with data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
- Proven track record of using AI to accelerate development and optimize code.
Nice-to-have
- Experience with open source projects.
- Familiarity with different styles of source control workflow and continuous integration.
- Experience designing and leading cross-functional initiatives.
Experience: Professional experience with search or vector databases.
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 Senior Software Engineer to join the Elasticsearch - Search Relevance 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 technical leader is responsible for contributing to the technical direction and vision for our search capabilities, including design and implementation of new search features, enhancements to 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 search engine 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 Elasticsearch search relevance. You'll identify and drive improvements 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
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You have implemented novel techniques in vector similarity on a search platform with a large user base or progressed the field of academic research in vector similarity information retrieval.
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Professional experience with search or vector databases, and you used HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.
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You have solid 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 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:
€85.600—€135.500 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 Senior Software Engineer - Vector Search - Elasticsearch role focuses on leading and contributing to the development of advanced search and vector similarity features in Elasticsearch, with an emphasis on Java expertise, search relevance, and collaborative, distributed teamwork.
- Vector search and similarity algorithms·High
- Core Java development and code quality·High
- Search relevance and feature enhancement·High
- Distributed and asynchronous team collaboration·High
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Vector Search and Similarity Algorithms
0–8 minStudy HNSW, IVF, and related algorithms, focusing on their application in search platforms and recent advancements.
Refresh Core Java Skills
8–15 minPractice writing idiomatic Java, review concurrency constructs, and revisit code review best practices.
Research Elasticsearch and Data Storage Technologies
15–22 minDeep dive into Elasticsearch's architecture and compare it with Solr, PostgreSQL, MongoDB, and Cassandra.
Prepare Examples of Distributed Teamwork
22–26 minGather concrete stories of working in asynchronous, distributed teams, highlighting communication and project ownership.
Outline AI-Driven Development Experiences
26–30 minList specific instances where you used AI tools to debug, optimize, or accelerate software development.
Talking points
, 6 itemsImplementing Vector Similarity Algorithms
You should be ready to discuss your experience with HNSW, IVF, or similar algorithms, as the role requires expertise in vector search at scale.
Java Proficiency and Code Review
Demonstrating deep knowledge of Java, including concurrency and modern features, is essential for contributing to Elasticsearch's codebase.
Improving Search Relevance
Prepare examples where you identified and drove improvements in search relevance, as this is a core responsibility.
Collaborative Development in Distributed Teams
Showcase your ability to work autonomously and collaboratively, especially in asynchronous, globally distributed environments.
Experience with Data Storage Technologies
Be ready to discuss your hands-on experience with Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra, as familiarity with these is expected.
Using AI to Accelerate Development
Share concrete examples of leveraging AI to debug, optimize, or accelerate software development, as this is highlighted in the requirements.
What to research
, 4 itemsVector Search Algorithms
Review HNSW, IVF, and other vector similarity algorithms, focusing on their implementation and optimization in search platforms.
Core Java and Concurrency
Refresh knowledge of Java concurrency constructs, standard libraries, and idiomatic coding practices relevant to large-scale systems.
Elasticsearch and Data Storage Technologies
Deepen understanding of Elasticsearch, Solr, PostgreSQL, MongoDB, and Cassandra, especially their architecture and use cases.
Distributed Team Collaboration
Prepare examples of working in globally distributed, asynchronous teams, including communication and project management strategies.
Questions to ask
, 6 itemsWhat are the current technical challenges or priorities for the Search Relevance team?
Why ask this? To understand the team's focus and how your skills can contribute.
How does the team approach collaboration and code review in a globally distributed environment?
Why ask this? To gauge expectations for remote and asynchronous work.
What is the process for proposing and implementing new search features or relevance improvements?
Why ask this? To clarify your potential impact and autonomy in the role.
How does the team leverage AI to accelerate development and optimize search capabilities?
Why ask this? To learn about the practical use of AI in the team's workflow.
What opportunities exist for contributing to open source or engaging with the broader Elasticsearch community?
Why ask this? To assess involvement in open source and community-driven development.
How are cross-functional initiatives managed and prioritized within the organization?
Why ask this? To understand how projects are coordinated across teams and functions.
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