Do you possess current expertise with Lucene, Elasticsearch, Solr, or similar search engines and are looking to drive search-based technology solutions for us?
About the Team
Our team is dedicated to unlocking the rich knowledge embedded within Elsevier’s content through our rich data platform; this empowers researchers, clinicians, and innovators worldwide to gain new insights, make informed decisions, and accelerate progress across research, healthcare, and life sciences. We lead the ongoing transformation of Elsevier’s vast, unstructured information into richly interconnected knowledge graphs that capture the full depth and nuance of scientific meaning. Through our dynamic knowledge discovery platform, we combine graph-powered agentic AI with advanced search technologies to deliver contextually relevant, trustworthy, and precise answers to researchers.
As part of the Search team, you'll contribute to the systems and infrastructure that fuel this mission. We focus on building scalable, reliable, and high-performance retrieval systems that accelerate innovation across Elsevier’s ecosystem.
The Role
We are looking for a Principal Software Engineer with extensive search experience that can design and implement complex search and retrieval systems, mentor team members, and help evolve our central search engineering architecture by collaborating closely with product, platform, and other engineering teams to deliver technical solutions, and high-throughput services with meaningful real-world impact.
Responsibilities
- Leading architectural design and ensure technical consistency.
- Helping lead our shared search platform – expanding content search, improving relevance via vector and lexical search techniques.
- Building world-class search systems to enhance users’ search experience.
- Automating processes to assist other teams.
- Collaborating on new ideas to optimize systems and engineering workflows.
- Building relationships with other engineering teams to identify and solve their pain points.
- Working across the stack, from development to infrastructure.
- Designing and developing scalable data processing workflows and microservices using Spark, Spark Streaming, and Airflow.
- Writing clean, modular, and testable code in Python, Java, or Scala, aligned with coding standards and architecture guidelines.
- Lead implementation of system components that span multiple services and modules.
- Diagnose and resolve complex technical issues across distributed systems and data workflows.
- Leading design discussions, code reviews, and architecture sessions to ensure software quality and maintainability.
- Developing and maintain data models to support analytical and operational use cases.
- Collaborate with cross-functional stakeholders to translate product requirements into reliable engineering solutions.
What We’re Looking For
- Current expertise with Lucene, Elasticsearch, Solr, or any other search engine, and have industry experience with Semantic Search.
- Proven track record building search systems at scale.
- Proficiency in batch processing technologies, including Spark, Spark Streaming, Airflow.
- Expertise in at least one of Java, Python, Scala.
- Deep understanding of distributed system design, data modeling, and performance tuning.
- Experience with test-driven development and CI/CD practices.
- Ability to independently drive technical outcomes from problem definition to deployment.
- Familiarity with Agile, Kanban, or other iterative development methodologies.
- Familiarity with vector/embedding-based search, KNN algorithms.
- Exposure to graph-based data models or knowledge graph architecture.
- Experience building internal platforms or developer-facing data tooling.
- Knowledge of observability best practices for data systems (e.g., metrics, logs, alerts).
Elsevier is a global leader in advanced information and decision support for science and healthcare. We believe that by working together with the communities we serve, we can shape human progress to go further, happen faster, and benefit all. We support continuous discovery and uphold the highest standards of content integrity, reliability, and reproducibility so the communities we serve can advance their field of science, healthcare or innovation with confidence. By combining high-quality content with powerful analytics, we transform complexity into clarity and deliver mission-critical insights that help professionals make better decisions when it matters most. We deliver insights that help research institutions, governments and funders achieve their goals.
U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $121,200 - $201,900.If performed in New York, the base pay range is $126,900 - $211,500.If performed in New York City, the base pay range is $138,400 - $230,700.If performed in Rochester, NY, the base pay range is $115,400 - $192,300.If performed in New Jersey, the base pay range is $136,213 - $217,587. This job is eligible for an annual incentive bonus.We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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Skills Required
- Current expertise with Lucene, Elasticsearch, Solr, or other search engines and Semantic Search
- Proven track record building search systems at scale
- Proficiency in batch and streaming processing: Spark, Spark Streaming, Airflow
- Expertise in at least one language: Java, Python, or Scala
- Deep understanding of distributed system design, data modeling, and performance tuning
- Experience with test-driven development and CI/CD practices
- Familiarity with vector/embedding-based search and KNN algorithms
- Exposure to graph-based data models or knowledge graph architecture
- Experience building internal platforms or developer-facing data tooling
- Knowledge of observability best practices for data systems (metrics, logs, alerts)
- Ability to lead architecture, design discussions, code reviews, and mentor team members
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
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Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.
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