Do you possess current expertise with Lucene, Elasticsearch, Solr, or similar search engines and are looking to drive search-based technology solutions for us?

Are you a Technology Leader with an expertise in Search based systems?

About The Role

We are looking for a Tech Lead with deep search experience to provide hands-on technical leadership for the Search Experience team. In this role, you will guide the design and delivery of scalable search and retrieval systems, lead a group of engineers, and serve as a key technical partner to product, platform, and research stakeholders.

You will balance writing high-quality code with leading technical execution — shaping architectural decisions, unblocking delivery, and ensuring our search platform evolves to meet the demands of diverse products and users. This role sits between senior engineers and principal-level leadership, with strong ownership of outcomes and day-to-day technical direction.

About the Team

Our team is dedicated to unlocking the rich knowledge embedded within Elsevier’s content through our rich data platform — empowering 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 Experience team, you’ll contribute to the systems and infrastructure that fuel this mission. We focus on building scalable, reliable, and high-performance retrieval and AI systems — including shared search platform capabilities, semantic and vector search, and AI-powered experiences — that accelerate innovation across Elsevier’s ecosystem.

Responsibilities

Providing technical leadership for the Search Experience team, guiding design and implementation of shared search and retrieval systems.

Owning the technical delivery of search platform initiatives, ensuring solutions meet requirements for scalability, relevance, reliability, and maintainability.

Leading our shared search platform — expanding content search and improving relevance through vector and lexical search techniques.

Designing and developing scalable search services, data processing workflows, and microservices using technologies such as Elasticsearch, Spark, and Airflow.

Writing clean, modular, and testable code in Python and/or Java, aligned with architecture guidelines and engineering standards.

Leading design discussions, code reviews, and architecture sessions to ensure software quality and maintainability.

Mentoring and supporting engineers through pairing, code reviews, and technical coaching.

Proactively identifying technical risks, dependencies, and bottlenecks, and drive them to resolution.

Contributing to cross-team alignment, ensuring the search platform integrates cleanly with broader product and AI ecosystems.

Requirements

Current expertise with Lucene, Elasticsearch, Solr, or similar search engines, with industry experience in semantic and lexical search. Only candidates with Search Technology will be considered for this role.

Demonstrated experience acting as a technical lead on complex backend or search platform systems.

Proven track record building and scaling search systems in production environments.

Current and extensive development skills in Python and/or Java; Scala is a plus.

Solid backend engineering fundamentals: API design, data modelling, distributed systems, and performance tuning.

Proven ability to balance hands-on development with technical leadership and cross-functional coordination.

Experience with Agile or Kanban teams, collaborating across functions.

Experience building or integrating AI/LLM-powered or GenAI applications.

Familiarity with vector/embedding-based search and KNN algorithms.

Exposure to graph-based data models or knowledge graph architecture.

Experience working on internal developer platforms or shared infrastructure used by multiple teams.

Knowledge of observability best practices for distributed 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 serv

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