At a Glance
- Tasks: Shape the future of AI by training advanced generative systems and optimising workflows.
- Company: Outlier, a leader in AI innovation with a focus on collaboration.
- Benefits: Freelance flexibility, remote work, and the chance to work on cutting-edge projects.
- Other info: Dynamic freelance role with opportunities to work on innovative AI solutions.
- Why this job: Join a team that’s redefining AI agents and make a real impact in tech.
- 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. Do you want to shape the future of autonomous agents like OpenClaw? 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.
Agentic AI Engineer (Freelance, Remote) (Cambridge) employer: Outlier AI
Outlier is an exceptional employer for those looking to make a significant impact in the AI field, particularly as a freelance Agentic AI Engineer. With a focus on innovative projects and collaboration with leading AI organisations, employees benefit from a flexible remote work culture that fosters creativity and growth. The opportunity to work on cutting-edge technology in a supportive environment ensures that team members can develop their skills while contributing to the future of autonomous agents.
StudySmarter Expert Advice🤫
We think this is how you could land Agentic AI Engineer (Freelance, Remote) (Cambridge)
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and engineering fields. Attend meetups, webinars, or online forums where you can chat with industry experts. You never know who might have a lead on your dream freelance gig!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI automation or complex systems integration. Make sure to highlight any experience with LLMs or multi-stage coordination tasks. This will make you stand out when applying through our website.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with backend engineering and how you've tackled real-world problems. Practise explaining complex concepts clearly, as communication is key in this field.
✨Tip Number 4
Don’t just apply blindly! Tailor your applications to each role, especially focusing on the specific skills mentioned in the job description. When you apply through our website, make sure your application reflects your understanding of the project and how you can contribute.
We think you need these skills to ace Agentic AI Engineer (Freelance, Remote) (Cambridge)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience in backend engineering and AI automation. We want to see how you've built production-grade software and tackled complex systems integration, so don’t hold back!
Be Specific:When detailing your past projects, be specific about the technologies you used and the challenges you faced. We love seeing clear examples of your work with languages like Python or JavaScript, and how you’ve handled multi-turn interactions.
Attention to Detail is Key:We’re all about precision here at StudySmarter. Make sure your application is free from typos and clearly structured. This shows us that you have the outstanding attention to detail we’re looking for!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Outlier AI
✨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 demonstrate your understanding of databases during the interview.
✨Showcase Your Experience
Prepare specific examples from your past work that highlight your experience with backend engineering and AI automation. Be ready to discuss how you've built production-grade software and handled complex system integrations.
✨Understand the Project Goals
Familiarise yourself with Outlier's mission and the types of projects they undertake. Being able to discuss how your skills can contribute to training advanced generative systems will show your genuine interest in the role.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving abilities and attention to detail. Practice explaining complex system behaviours clearly, as this is crucial for providing high-density feedback on AI agents.
