At a Glance
- Tasks: Shape the future of AI agents by providing human feedback and optimising complex workflows.
- Company: Outlier, a leader in AI innovation with a focus on collaboration.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting projects and career advancement opportunities.
- Why this job: Join us to train advanced generative systems and make a real impact in AI.
- Qualifications: 2+ years in backend engineering or AI automation, strong coding skills required.
The predicted salary is between 50000 - 70000 € 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.
AI Agent Developer (Remote) in Fraserburgh employer: Employer near you
Outlier is an exceptional employer for AI Agent Developers, offering a dynamic remote work environment that fosters innovation and collaboration with leading AI organisations. Our culture prioritises employee growth through continuous learning opportunities and hands-on experience with cutting-edge technologies, ensuring you can make a meaningful impact in shaping the future of autonomous agents. Join us to be part of a forward-thinking team that values your expertise and encourages creative problem-solving in a supportive atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land AI Agent Developer (Remote) in Fraserburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and software development communities. Attend meetups, webinars, or even online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI agents or backend engineering. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with languages like Python or Java, and how you've tackled complex systems integration. Practice common interview questions to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, get that application in and let’s shape the future of AI together!
We think you need these skills to ace AI Agent Developer (Remote) in Fraserburgh
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Agent Developer role. Highlight your experience in backend engineering and any relevant projects you've worked on that showcase your skills in AI automation and complex systems integration.
Showcase Your Skills:Don’t just list your technical skills; demonstrate them! Include specific examples of how you've used languages like Python or JavaScript in real-world applications, especially in live environments.
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. We want to see your passion for AI and how you can contribute to our projects, so make sure to express that enthusiasm without rambling.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Employer near you
✨Know Your Tech Inside Out
Make sure you’re well-versed in the programming languages mentioned in the job description, like Python or JavaScript. Brush up on your SQL skills too, as you might be asked to solve real-world problems using these technologies during the interview.
✨Showcase Your Experience
Prepare specific examples from your past work that demonstrate your ability to build and maintain production-grade software. Highlight any projects where you’ve worked with complex systems integration or AI automation, as this will resonate well with the interviewers.
✨Understand the Project Goals
Familiarise yourself with Outlier’s mission and the types of AI agents they develop. Being able to discuss how your skills can contribute to shaping autonomous agents like OpenClaw will show your genuine interest and alignment with their goals.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects or challenges they face. This not only shows your enthusiasm but also your critical thinking skills, which are essential for a role focused on multi-step agent coordination and optimisation.
