At a Glance
- Tasks: Build and ship AI-powered features in a dynamic, cross-functional team.
- Company: Join a global leader in information and analytics, driving innovation in science and healthcare.
- Benefits: Enjoy flexible hours, generous vacation, and a comprehensive pension plan.
- Other info: Be part of a culture that values well-being, collaboration, and career growth.
- Why this job: Make a real impact by creating intelligent systems that improve health outcomes.
- Qualifications: 3+ years in software engineering with experience in LLM-powered applications.
The predicted salary is between 60000 - 80000 £ per year.
Are you excited about building intelligent systems powered by innovative AI technologies? Do you enjoy creating solutions that turn complex data into impactful outcomes?
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 an 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:
- Build prototypes and proofs of concept and ship agentic AI solutions to production standard within a defined technical approach.
- Implement and test tool use, retrieval pipelines, and agent workflows.
- Contribute to evaluation, observability and guardrails for agentic systems.
- Integrate AI capabilities into existing enterprise workflows and systems.
- Maintain high code quality and documentation so patterns can be reused.
- Flag technical risks and blockers early.
- Interface with technical peers to finalise requirements and complete moderately complex bug fixes.
- Build solutions for reuse, contributing to patterns, reference implementations, and starter kits so work done in one function can be picked up by another.
- Instrument solutions to capture outcome data against baselines.
- Work alongside host-function stakeholders to ensure the build fits real workflows, not assumed ones.
- Support handover and capability-building in the host function so the solution is owned and operable after the squad moves on.
- Keep abreast of new technology developments.
- Take on related responsibilities as the squad's needs evolve.
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).
- Education: BS in Engineering, Computer Science, or equivalent.
- 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.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. 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.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Please read our Candidate Privacy Policy. 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.
AI Engineer employer: Elsevier
At Elsevier, we pride ourselves on fostering a culture of innovation and collaboration, making us an exceptional employer for AI Engineers. Our commitment to employee well-being is reflected in our flexible working hours, comprehensive benefits including generous vacation entitlement and a robust pension plan, and numerous opportunities for personal and professional growth. Join us in a dynamic environment where your contributions directly impact global health outcomes and advance scientific research.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Elsevier or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Elsevier.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Elsevier.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Elsevier that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Elsevier.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Elsevier and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Elsevier
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Elsevier uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
