Senior Software Engineer I – Search and AI Platform
About the Team
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.
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.
What We’re Looking For
- 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 Have
- Experience operationalizing LLMs or building internal AI platforms.
- Familiarity with observability practices (metrics, logging, alerts).
- Exposure to knowledge graphs or semantic search systems.
U.S. National Base Pay Range: $86,600 - $144,400. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $90,900 - $151,700.If performed in New Jersey, the base pay range is $102,333 - $163,467. This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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Skills Required
- 4-6 years of software engineering experience
- Experience contributing to technical architecture for large-scale platforms or services
- Understanding of software development methodologies and data modeling principles
- Deep expertise in Python and Java
- Backend development experience
- Familiarity with modern AI and LLM tools and frameworks, such as LangChain and LangGraph
- Experience with Kubernetes, including EKS, and cloud-native architectures
- Experience building scalable backend systems and APIs
- Experience mentoring engineers and contributing to architectural decisions
- Ability to collaborate across functions in an Agile or Kanban environment
- Experience operationalizing LLMs or building internal AI platforms
- Familiarity with observability practices, including metrics, logging, and alerts
- Exposure to knowledge graphs or semantic search systems
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
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Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.
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