Are you excited about building intelligent systems powered by cutting-edge AI technologies?
Do you enjoy designing models that turn complex data into impactful solutions?
About the team:
Embedded Innovation Teams are cross-functional squads embedded within our segments to rapidly turn internal AI experimentation into validated, reusable solutions, building the capabilities we need to deliver customer value and growth. We work problem-first rather than tool-first, directly inside segment and function teams, improving the internal workflows that help our people deliver better outcomes for customers, faster.
About the role:
As a Senior AI Engineer, you will build and ship AI-powered features as part of a cross-functional Innovation Squad, working inside a business function. You will deliver the set technical direction to production standard, working autonomously within a defined problem, building and testing tool use, retrieval pipelines, and agent workflows, integrating AI capabilities into enterprise systems, and contributing to evaluation, observability, and guardrails.
You will hold a high bar on code quality, flag risks and blockers early, and work alongside host-function stakeholders to make sure what you build fits real workflows, not assumed ones. You'll also support handover and capability-building so the solution is owned and operable after the squad moves on.
Key Responsibilities:
- Building prototypes and proofs of concept and ship agentic AI solutions to production standards within a defined technical approach.
- Implementing and testing tool use, retrieval pipelines, and agent workflows.
- Contributing to evaluation, observability, and guardrails for agentic systems.
- Integrating AI capabilities into existing enterprise workflows and systems.
- Maintaining high code quality and documentation so patterns can be reused.
- Flagging technical risks and blockers early.
- Interface with technical peers to finalize requirements and complete moderately complex bug fixes.
- Building solutions for reuse, contributing to patterns, reference implementations and starter kits so work done in one function can be picked up by another.
- Implementing solutions to capture outcome data against baselines.
- Work alongside host-function stakeholders to ensure the build fits real workflows, not assumed ones.
- Supporting handover and capability-building in the host function so the solution is owned and operable after the squad moves on.
Requirements:
- Engineering experience: 3+ years in software engineering, with hands-on experience building LLM-powered applications in production (RAG, tool-augmented agents, or agentic workflows).
- Ways of working: Comfortable working autonomously within a defined problem and pushing back when something doesn't make sense, and delivering in short, time-boxed cycles where validated outcomes matter more than perfect solutions.
- Agentic AI / LLMs: Building RAG pipelines, tool-augmented agents, and agentic workflows; familiar with prompt engineering, context management, evaluation, and observability.
- Agent fundamentals: Understands how agents use memory, tools, and retrieval to complete multi-step tasks.
- Enterprise integration: Integrating AI into existing systems via APIs and data pipelines.
- Cloud: AWS, Azure or GCP.
- Delivery: CI/CD, modern SDLC, TDD and code review.
- Data: Working with relational, columnar and vector stores, grounded in sound data-modelling principles.
- Languages: Python, Java, TypeScript/JavaScript, SQL and relevant AI SDKs.
- Communication: Clear written and verbal communication with technical peers and stakeholders.
- Measurement: Instrumenting solutions to capture usage, productivity and quality metrics against established baselines.
Why Join Us?
Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply.
Work in a way that works for you
We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
- Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Working for you
We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- Comprehensive Pension Plan
- Generous vacation entitlement and option for sabbatical leave
- Maternity, Paternity, Adoption and Family Care leave
- Personal Choice budget
- Internal communities and networks
- Various employee discounts
- Recruitment introduction reward
- Employee Assistance Program (global)
About the business-
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. 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. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
U.S. National Base Pay Range: $86,600 - $144,400. 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.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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Skills Required
- 3+ years of software engineering experience
- Hands-on experience building LLM-powered applications in production, including RAG, tool-augmented agents, or agentic workflows
- Experience building RAG pipelines, tool-augmented agents, and agentic workflows
- Familiarity with prompt engineering, context management, evaluation, and observability
- Understanding of agent memory, tools, retrieval, and multi-step task completion
- Experience integrating AI into existing systems through APIs and data pipelines
- Experience with AWS, Azure, or GCP
- Experience with CI/CD, modern SDLC, TDD, and code review
- Experience with relational, columnar, and vector stores and sound data-modeling principles
- Proficiency in Python, Java, TypeScript or JavaScript, SQL, and relevant AI SDKs
- Clear written and verbal communication with technical peers and stakeholders
- Experience instrumenting solutions to measure usage, productivity, and quality against established baselines
- Ability to work autonomously within defined problems and deliver in short, time-boxed cycles
Elsevier Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Elsevier and has not been reviewed or approved by Elsevier.
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Leave & Time Off Breadth — Feedback suggests paid time off spans vacation, holidays, sick days, bereavement, military leave, and volunteer time. Family-related leave options are also emphasized as part of the package.
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Healthcare Strength — Feedback suggests medical, dental, vision, life insurance, wellness initiatives, and an EAP form a comprehensive health offering. Gym support and wellbeing hubs reinforce an ongoing health and wellness focus.
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Retirement Support — Feedback suggests retirement programs include a 401(k)/retirement plan and pension options, with long-term savings vehicles such as an employee stock purchase plan also available. These elements contribute to a sense of financial security beyond base pay.
Elsevier Insights
What We Do
Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals, empowering them to make better decisions, and deliver better care. Because informed decisions lead to better outcomes, Elsevier is a leader in information and analytics for customers across the global research and health ecosystems. Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.
