At a Glance
- Tasks: Join us in shaping the future of AI by training advanced generative systems.
- Company: Outlier, a leader in AI innovation and collaboration.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting challenges and career advancement.
- Why this job: Make a real impact on cutting-edge AI projects and enhance your skills.
- Qualifications: 2+ years in backend engineering and strong programming skills required.
The predicted salary is between 50000 - 60000 € per year.
About the Project
Outlier helps the world's most innovative companies improve their AI agents by providing human feedback. We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents. Our projects focus on teaching these systems how to design, coordinate, and optimize complex, real-world architectural workflows.
Whether you are a passionate orchestration guru or experienced software developer — we want you to help us train the world's most advanced generative systems.
Ideal Qualifications
- 2+ years of experience in backend engineering, AI automation, or complex systems integration.
- Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting).
- Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases.
- Practical experience building for live, non-mocked environments and handling multi-turn system interactions.
- Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors.
Nice to have
- Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output.
- Hands-on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems.
- High level of comfort implementing persistent state and session discovery using MEMORY.md to track agent progress.
- Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.
LLM Integration Engineer (Remote) (Liverpool) employer: Outlier AI
At Outlier, we pride ourselves on being an exceptional employer, offering a dynamic remote work environment that fosters innovation and collaboration. Our culture is built on continuous learning and growth, providing employees with ample opportunities to enhance their skills in cutting-edge AI technologies while working alongside industry leaders. With a focus on meaningful projects that shape the future of autonomous agents, we ensure that our team members are not only valued but also empowered to make a significant impact in the field.
StudySmarter Expert Advice🤫
We think this is how you could land LLM Integration Engineer (Remote) (Liverpool)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and engineering space on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or complex systems integration. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past experiences with backend engineering and AI automation.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining our team. It shows initiative and enthusiasm, which we really appreciate!
We think you need these skills to ace LLM Integration Engineer (Remote) (Liverpool)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the LLM Integration Engineer role. Highlight your experience in backend engineering and any projects that showcase your skills in AI automation or complex systems integration. We want to see how your background aligns with what we're looking for!
Showcase Your Skills:When writing your application, don’t just list your skills—show us how you've used them! Include specific examples of projects where you’ve built production-grade software or worked with major programming languages like Python or JavaScript. This helps us understand your hands-on experience.
Be Clear and Concise:We appreciate clarity! Make sure your application is easy to read and straight to the point. Use bullet points for key achievements and keep your language professional yet approachable. Remember, we’re looking for outstanding attention to detail!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Outlier AI
✨Know Your Tech Inside Out
Make sure you brush up on your backend engineering skills and the programming languages mentioned in the job description. Be ready to discuss your experience with Python, JavaScript, or any other relevant language, and how you've used them in real-world projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex systems integration challenges. Think about specific instances where you built production-grade software or optimised workflows, and be ready to explain your thought process during those situations.
✨Demonstrate Attention to Detail
Since the role requires a keen eye for detail, come prepared with examples that highlight your ability to provide clear technical feedback. Discuss how you've identified subtle failures in past projects and what steps you took to resolve them.
✨Familiarise Yourself with Real-World Applications
Research how LLMs are being integrated into live tools and applications. Be ready to discuss any hands-on experience you have with APIs or tools like Supabase and Gmail, and how they relate to solving real-world problems in AI.
