To benefit humanity, Elsevier helps professionals and institutions advance healthcare, improve performance, and progress science. Elsevier employs approximately 7,500 people and se
Software Engineering Lead
Location
United States
Posted
9 days ago
Salary
$115.4K - $230.7K / year
Seniority
Lead
No structured requirement data.
Job Description
Software Engineering Lead
Elsevier
Role Description We are seeking a Software Engineering Lead to provide hands-on technical leadership for the AI Platform (US) team. In this role, you will guide the design and delivery of shared AI services, lead a group of engineers, and act as a key technical partner to product, research, and platform stakeholders. You will balance writing high-quality code with leading technical execution, shaping designs, unblocking delivery, and ensuring the platform scales across many consumers and use cases. This role sits between senior engineers and principal-level leadership, with strong ownership of outcomes and day-to-day technical direction. Responsibilities - Providing technical leadership for the AI Platform team, guiding design and implementation of shared AI services and components. - Owning the technical delivery of platform initiatives, ensuring solutions meet requirements for scalability, reliability, security, and maintainability. - Designing, developing, and maintaining backend services and APIs, primarily in Python, with some Java. - Translating architectural guidance into concrete, well-structured implementations and iterative delivery plans. - Partnering with product managers, research, and downstream engineering teams to turn AI prototypes into production-ready platform capabilities. - Establishing and enforcing engineering best practices across the team, including testing, CI/CD, observability, and operational readiness. - Reviewing designs and code, providing clear, constructive feedback and maintaining a high-quality bar. - Mentoring and supporting engineers through pairing, code reviews, and technical coaching. - Operating within a Kubernetes (EKS) environment, contributing to deployment, scaling, and runtime stability of AI services. - Proactively identifying technical risks, dependencies, and bottlenecks, and driving them to resolution. - Contributing to cross-team alignment, ensuring the AI Platform integrates cleanly with broader platform and product ecosystems. Qualifications - Extensive professional software engineering experience. - Demonstrated experience acting as a technical lead on complex backend or platform systems. - Proficiency in Python, with working knowledge of Java. - Solid backend engineering fundamentals: API design, data modelling, concurrency, and distributed systems. - Experience building or integrating AI/LLM-powered systems, and familiarity with modern AI frameworks (e.g., LangChain, LangGraph). - Hands-on experience with Kubernetes (EKS) and cloud-native application development. - Proven ability to balance hands-on development with technical leadership and coordination. - Experience working in Agile or Kanban teams, collaborating across functions. Benefits - This job is eligible for an annual incentive bonus. - We offer country-specific benefits. Click here to access benefits specific to your location. Company Description Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. In addition to publishing, Elsevier offers a suite of digital solutions and services to support researchers, scientists, and professionals in their work. They provide online platforms like ScienceDirect, Scopus, and Mendeley, which offer access to a vast repository of scholarly articles, research papers, and other scientific content.
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