Principal Software Engineer - Vector Search - Elasticsearch

Elastic
Full-timeFull-stackIreland
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At a glance

Employment type
Full-time
Location
Ireland
Workplace
On-site
Category
Full-stack

Technologies & skills

Primary technologies

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 designing and implementing new features, improving existing functionalities, and resolving bugs in 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 in Elasticsearch's vector similarity implementation.
  • Collaborate with community members on issues and pull requests.

Key requirements

Must-have

  • Experience implementing techniques in vector similarity on a search platform.
  • 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.
  • Excellent verbal and written communication skills.

Nice-to-have

  • Experience with Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
  • Experience collaborating over the internet and asynchronous collaboration.
  • Familiarity with open source projects and source control workflows.

Experience: Not specified

Role signals

Technical focus
Full-stack
Architecture / system design
Indicated in the listing
Hands-on vs management
Hands-on

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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

  • Lead initiatives within Elasticsearch to produce an industry-leading vector database offering, supplying unparalleled speed and relevance in search.

  • 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.

  • Work with a globally distributed team of experienced engineers focused on the vector search capabilities of Elasticsearch.

  • 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.

  • 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.

  • Write idiomatic modern Java -- Elasticsearch is 99.8% Java!

What You Bring Along

  • 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.

  • Professional experience with vector similarity and vector databases, and you used HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • You have a proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes.

  • You possess the ability to collaborate across functions and teams and seamlessly transition between different projects, codebases, or teams based on business priorities

  • You work autonomously and can drive decisions and results in a distributed team by leveraging asynchronous, direct, and transparent communication.

Bonus Points

  • You've built things with Elasticsearch before.

  • You've worked with open source projects and are familiar with different styles of source control workflow and continuous integration.

  • Experience with data storage technology.

  • 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.

  • Competitive pay based on the work you do here and not your previous salary

  • Health coverage for you and your family in many locations

  • Ability to craft your calendar with flexible locations and schedules for many roles

  • Generous number of vacation days each year

  • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service

  • Up to 40 hours each year to use toward volunteer projects you love

  • 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 - Vector Search - Elasticsearch role centers 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 similarity search algorithms and implementation·High
  • Advanced Java development and concurrency·High
  • Distributed and asynchronous team collaboration·High
  • Open source contribution and community engagement·High

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review Vector Search Algorithms and Implementations

    0–8 min

    Study HNSW, IVF, and other vector similarity algorithms, focusing on their use in Elasticsearch and similar platforms.

  2. Refresh Advanced Java and Concurrency Concepts

    8–15 min

    Brush up on Java concurrency, data structures, and idiomatic coding practices relevant to large-scale systems.

  3. Prepare Examples of Open Source and Distributed Collaboration

    15–20 min

    Gather concrete stories of contributing to open source projects and working in globally distributed teams.

  4. Research Elasticsearch’s Current Vector Search Features

    20–25 min

    Explore the latest vector search capabilities and open issues in the Elasticsearch GitHub repository.

  5. Draft Role-Specific Questions

    25–30 min

    Prepare thoughtful questions about the team’s technical challenges, collaboration style, and open source engagement.

Likely questions

, 7 items

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

Talking points

, 6 items
  • Implementing Vector Similarity Search

    You will need to demonstrate experience with vector search algorithms (e.g., HNSW, IVF) and discuss how you have applied or advanced these techniques in large-scale search platforms.

  • Core Java Expertise

    The role requires writing idiomatic, modern Java and leveraging advanced features such as concurrency constructs and data structures; be ready to discuss relevant projects.

  • Leading Technical Initiatives

    You are expected to guide projects from design to delivery, so prepare examples of how you have led technical initiatives, made architectural decisions, and driven results.

  • Collaborative Open Source Development

    The position involves working with a global team and the open source community; be prepared to share experiences contributing to open source, handling pull requests, and collaborating asynchronously.

  • Cross-Technology Data Storage Experience

    Familiarity with multiple data storage technologies (Elasticsearch, Solr, PostgreSQL, MongoDB, Cassandra) is valued; discuss how you have leveraged or compared these systems.

  • Communication in Distributed Teams

    Excellent communication is essential for remote, asynchronous collaboration; prepare examples of how you have communicated complex ideas and resolved issues in distributed environments.

What to research

, 4 items
  • Vector Similarity Search Algorithms

    Review HNSW, IVF, and other vector search algorithms, focusing on their implementation and optimization in large-scale systems.

  • Modern Java and Concurrency

    Refresh your knowledge of advanced Java features, concurrency constructs, and best practices for writing scalable, maintainable code.

  • Open Source Contribution Workflow

    Familiarize yourself with contributing to large open source projects, including code review processes, pull requests, and community engagement.

  • Distributed Team Communication

    Prepare examples of effective asynchronous collaboration and communication in globally distributed teams.

Questions to ask

, 6 items
  1. What 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.

  2. How does the team approach consensus and decision-making for major architectural changes?

    Why ask this? To gauge the collaborative and leadership dynamics within the team.

  3. What is the typical workflow for contributing new features or bug fixes to Elasticsearch?

    Why ask this? To clarify expectations around development and open source contribution.

  4. How does the team balance innovation in search algorithms with the need for stability and backward compatibility?

    Why ask this? To understand the product and engineering priorities.

  5. What tools and practices does the team use to facilitate effective asynchronous collaboration?

    Why ask this? To assess the maturity of remote work practices and how you can integrate smoothly.

  6. How does the team engage with the broader open source community and handle external contributions?

    Why ask this? To learn about community involvement and expectations for open source engagement.

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Apply NowApply before: 27 Sep 2026