Technology Leader

Elsevier Inc.
United States
12 days ago
Apply on www.thejobnetwork.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Java (Programming Language) Agile Methodology Artificial Intelligence Airflow Automated Storage and Retrieval Systems Apache Lucene Software Quality Code Review Encodings Decision Support Systems Distributed Data Store Distributed Systems
+12 more
Elasticsearch Python (Programming Language) Performance Tuning Search Technologies Apache Solr Apache Spark Generative AI Backend Search Engines Api Design Data Pipelines Microservices

Job description

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

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

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.thejobnetwork.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:37 min

Optimizing technical profiles for AI sourcing and recruitment

Mina Golesorkhi Mina Golesorkhi · World Congress 2026 Europe

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

3:17 min

Optimizing character encoding with Kim variable byte encoding

Douglas Crockford Douglas Crockford · World Congress 2024

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

2:01 min

Exploring foundational expertise in traditional optimization and machine learning

Eric Enge · Coffee With Developers

1:12 min

Choosing TypeScript for complex backend applications

Maximilian Otto Maximilian Otto · World Congress 2024

Videos

See all

Related articles

See all