Are you a collaborative Agentic AI Engineer looking to work for a mission driven global organization?
About the team: The Elsevier Healthcare Education (EHE) Data and Content Software Engineering team is responsible for building and maintaining scalable content ingestion pipelines that power critical health education products. Our work enables flagship platforms such as Sherpath and HESI, ensuring high-quality, reliable, and timely delivery of educational content to learners and educators worldwide. We focus on developing robust, efficient systems that transform and manage complex data, supporting innovation across Elsevier’s health education ecosystem.
https://evolve.elsevier.com/education/
About the Role: We are seeking a Principal Software Engineer to join our team and play a key role in designing and delivering scalable, high-impact software solutions. In this role, you will lead the development of advanced content ingestion and processing systems, driving architectural decisions and engineering best practices across the team. You will collaborate closely with cross-functional partners, mentor engineers, and contribute to building resilient, high-performance platforms that support mission-critical products. This position offers the opportunity to influence technical strategy, champion innovation, and shape the future of content engineering within Elsevier Health Education.
Requirements.
Agentic AI & Advanced Tooling:
• Experience designing, building, or integrating agentic AI systems (e.g., autonomous workflows, multi-step reasoning agents, AI copilots).
• Hands-on experience with LLMs and orchestration frameworks (e.g., LangChain, OpenAI APIs, or similar).
• Ability to design tool-augmented agents (function calling, retrieval-augmented generation, memory systems, planning/execution loops).
• Experience with prompt engineering, evaluation, and guardrails for production-grade AI systems.
• Understanding of AI system architecture, including latency, cost optimization, observability, and reliability of agent workflows.
• Familiarity with vector databases, embeddings, and retrieval systems.
• Experience integrating AI capabilities into enterprise systems and developer workflows.
• Knowledge of responsible AI practices, including safety, bias mitigation, and governance.
Responsibilities:
- Lead the design and development of agentic AI systems
Architect and deliver autonomous workflows, multi-step reasoning agents, and AI copilots that solve complex business problems across the organization. - Define and implement LLM-powered architectures
Design scalable solutions leveraging large language models, orchestration frameworks (e.g., LangChain, OpenAI APIs), and modular service patterns to enable reusable AI capabilities. - Build and optimize tool-augmented agents
Develop agents that effectively utilize function calling, retrieval-augmented generation (RAG), memory systems, and planning/execution loops to perform reliable, context-aware tasks. - Establish best practices for prompt engineering and evaluation
Create standardized approaches for prompt design, testing, benchmarking, and continuous improvement to ensure high-quality outputs in production environments. - Implement production-grade guardrails and safety mechanisms
Design and enforce controls for hallucination mitigation, output validation, policy compliance, and safe execution of AI-driven workflows. - Drive AI system performance and reliability
Optimize latency, throughput, and cost efficiency of AI systems while ensuring high availability, observability, and fault tolerance across agent workflows. - Design and manage retrieval systems
Architect solutions using embeddings, vector databases, and hybrid search techniques to enable accurate, scalable knowledge retrieval. - Integrate AI capabilities into enterprise platforms
Embed AI services into existing products, APIs, and developer workflows, ensuring seamless interoperability with enterprise systems and data sources. - Lead technical strategy and cross-functional alignment
Partner with product, data, and engineering leaders to define AI roadmaps, prioritize initiatives, and align solutions with business objectives. - Champion responsible AI practices
Ensure systems adhere to standards for fairness, bias mitigation, transparency, and governance, while meeting regulatory and organizational compliance requirements. - Mentor and elevate engineering teams
Provide technical leadership, guide architectural decisions, and mentor engineers in building scalable, maintainable AI systems. - Continuously evaluate emerging technologies
Stay at the forefront of advancements in AI/ML, agent frameworks, and tooling, and drive adoption of innovations that create competitive advantage.
Elsevier employs 10,000 people worldwide, including over 2,500 technologists. We have supported the work of our research and health partners for more than 140 years. Growing from our roots in publishing, we offer knowledge and valuable analytics that help our users make breakthroughs and drive societal progress.
Digital solutions such as ScienceDirect, Scopus, SciVal, ClinicalKey and Sherpath support strategic research management, R&D performance, clinical decision support, medical education, and nursing education. Researchers and healthcare professionals rely on over 2,800 journals, including The Lancet and Cell; 46,000+ eBook titles; and iconic reference works, such as Gray's Anatomy. With the Elsevier Foundation and our external Inclusion & Diversity Advisory Board, we work in partnership with diverse stakeholders to advance inclusion and diversity in science, research and healthcare in developing countries and around the world.
Elsevier is part of RELX a global provider of information-based analytics and decision tools for professional and business customers.
U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. 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
- Experience designing, building, or integrating agentic AI systems (autonomous workflows, multi-step reasoning agents, AI copilots)
- Hands-on experience with LLMs and orchestration frameworks (e.g., LangChain, OpenAI APIs)
- Ability to design tool-augmented agents using function calling, RAG, memory systems, and planning/execution loops
- Experience with prompt engineering, evaluation, and production-grade guardrails
- Understanding of AI system architecture including latency, cost optimization, observability, and reliability
- Familiarity with vector databases, embeddings, and retrieval systems
- Experience integrating AI capabilities into enterprise systems and developer workflows
- Knowledge of responsible AI practices, including safety, bias mitigation, and governance
- Proven technical leadership and experience mentoring engineering teams
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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