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: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with potential to work on exciting, real-world AI challenges.
- Why this job: Join a cutting-edge team and make a real impact in AI technology.
- Qualifications: 2+ years in backend engineering or AI automation; strong coding skills required.
The predicted salary is between 60000 - 80000 € 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 Orchestration Engineer (Remote) in Northampton employer: Outlier AI
Outlier is an exceptional employer that fosters a collaborative and innovative work culture, allowing you to shape the future of AI technology from the comfort of your home. With a strong emphasis on employee growth, we provide opportunities for continuous learning and development in cutting-edge projects, ensuring that your contributions directly impact the advancement of autonomous agents. Join us to be part of a forward-thinking team that values your expertise and creativity in a dynamic remote environment.
StudySmarter Expert Advice🤫
We think this is how you could land AI Agent Orchestration Engineer (Remote) in Northampton
✨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 involving backend engineering or AI automation. This is your chance to demonstrate your expertise in building production-grade software and handling complex systems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with languages like Python or JavaScript, and how you've tackled real-world problems with multi-turn system interactions. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your orchestration skills and experience with live tools, and let’s shape the future of AI together!
We think you need these skills to ace AI Agent Orchestration Engineer (Remote) in Northampton
Some tips for your application 🫡
Show Your Passion:Let us see your enthusiasm for AI and orchestration! In your application, share why you're excited about shaping the future of autonomous agents. A personal touch can really make you stand out.
Highlight Relevant Experience:Make sure to showcase your backend engineering or AI automation experience. We want to know how your skills align with our needs, so don’t hold back on those impressive projects you've worked on!
Be Clear and Concise:When writing your application, clarity is key. Use straightforward language to explain your technical skills and experiences. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
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'll likely be asked to demonstrate your understanding of databases and how they integrate with AI systems.
✨Showcase Your Experience
Prepare specific examples from your past work that highlight your experience in backend engineering and AI automation. Be ready to discuss how you've built production-grade software and handled complex system integrations, as this will show you can hit the ground running.
✨Understand the Project Goals
Familiarise yourself with Outlier's mission and the projects they’re working on, especially around autonomous agents. This will help you align your answers with their goals and demonstrate your genuine interest in shaping the future of AI.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the team’s current challenges. This not only shows your enthusiasm but also your critical thinking skills. For instance, ask about the types of multi-stage coordination tasks they’re currently tackling or how they measure success in their AI projects.
