Senior Software Engineer I

RELX•Philadelphia, PA

About The Position

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. As part of this mission, the AI Platform team is focused on building reusable generative AI capabilities that can be embedded across products and platforms. We create scalable, secure, and production-ready AI services — enabling downstream teams to integrate cutting-edge GenAI features with confidence. The Role We are seeking a Senior Software Engineer I with a passion for generative AI and platform architecture. In this role, you will drive architectural decision and set engineering standard and implement robust systems to deliver reusable AI services and components, collaborating closely with cross-functional stakeholders to solve meaningful challenges. You will also contribute to mentor other engineers and help evolve our engineering practices.

Requirements

4-6 years of software engineering experience.
Proven experience contributing to technical architecture for large-scale platforms or services.
Solid understanding of software development methodologies and data modeling principles.
Deep expertise in Python and Java.
Proficiency in backend development and familiarity with modern AI/LLM tools and frameworks (e.g., LangChain, LangGraph).
Experience with Kubernetes (EKS) and cloud-native architectures.
Proven track record building scalable backend systems and APIs.
Experience mentoring engineers and contributing to architectural decisions.
Ability to work collaboratively across functions in an Agile or Kanban environment.

Nice To Haves

Experience operationalizing LLMs or building internal AI platforms.
Familiarity with observability practices (metrics, logging, alerts).
Exposure to knowledge graphs or semantic search systems.

Responsibilities

Leading architectural design and ensure technical consistency.
Designing, developing, and maintain generative AI services and reusable components using mostly Python and a little bit Java.
Defining and promote best practices in engineering, including scalability, observability, testing, and CI/CD.
Contributing to system designs spanning multiple services and modules, aligning with architectural best practices.
Collaborating with product, platform, and research teams to translate AI prototypes into production-ready capabilities.
Working within a Kubernetes (EKS) environment to deploy scalable, containerized applications.
Leading the resolution of complex technical challenges across distributed systems.
Mentoring less-senior developers on engineering principles, GenAI patterns, and platform development.
Participating in code reviews, architecture sessions, and cross-team initiatives to ensure quality and maintainability.
Staying informed of the latest developments in generative AI and advocate for responsible integration into product ecosystems.