Artificial Intelligence Engineer – Senior Software Engineer II
Join Elsevier’s technology team. We’re seeking a Senior Software Engineer II with a passion for generative AI and platform architecture to design and implement robust systems delivering reusable AI services and components.
About the Team
Working in technology at Elsevier means that your work really does matter – it changes lives. Our technologists have applied new machine learning models to reduce gender biases against women in academia and developed technology to help medical professionals diagnose conditions that may have otherwise been missed. Whether you’re supporting the business to be more efficient, building better infrastructure, or creating products for our customers, there’s always a new challenge to solve.
Responsibilities
- Design, develop, and maintain generative AI services and reusable components using Python and Java.
- Work within a Kubernetes (EKS) environment to deploy scalable, containerized applications.
- Contribute to system designs spanning multiple services and modules, aligning with architectural best practices.
- Collaborate with product, platform, and research teams to translate AI prototypes into production‑ready capabilities.
- Build and optimize CI / CD pipelines and implement test‑driven development practices.
- Lead the resolution of complex technical challenges across distributed systems.
- Mentor less‑senior developers on engineering principles, GenAI patterns, and platform development.
- Participate in code reviews, architecture sessions, and cross‑team initiatives to ensure quality and maintainability.
- Stay informed of the latest developments in generative AI, and advocate for responsible integration into product ecosystems.
Requirements
5+ years of software engineering experience.Deep expertise in Python and Java.Strong experience with Kubernetes (EKS) and cloud‑native architectures.Proven track record building scalable backend systems and APIs.Familiarity with foundational GenAI tools (e.g., HuggingFace, LangChain, vector databases, prompt engineering).Solid understanding of software development methodologies and data modeling principles.Experience mentoring engineers and contributing to architectural decisions.Ability to work collaboratively across functions in an Agile or Kanban environment.Experience operationalizing LLMs or building internal AI platforms is a plus.Familiarity with observability practices (metrics, logging, alerts) is a plus.Exposure to knowledge graphs or semantic search systems is desirable.Work Environment
This is a hybrid role. Our teams operate in a flexible hybrid work model, combining in‑person collaboration with remote flexibility. You’ll be expected to participate in regular team meetings and engineering rituals in line with your team’s cadence.
Benefits
Private Medical / Dental PlanSavings FundLife InsuranceMeal / Grocery VoucherAbout the Business
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. What you do every day will help advance science and healthcare to advance human progress.
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