At a Glance
- Tasks: Own projects from concept to deployment and build reliable AI systems.
- Company: Join a leading AI build project with Russell Tobin in Greater London.
- Benefits: Competitive salary and the chance to work on cutting-edge AI technology.
- Other info: Collaborate with engineering teams in a dynamic and innovative environment.
- Why this job: Make an impact by deploying real-world LLM systems across various products.
- Qualifications: Strong Python skills and experience in deploying LLM systems in production.
The predicted salary is between 60000 - 80000 € per year.
Russell Tobin is looking for skilled AI Operators in Greater London to join a major AI build project. This role focuses on deploying real-world LLM and agent-based systems across various products.
Key responsibilities include:
- Owning projects from concept to deployment
- Building reliable AI systems
- Collaborating with engineering teams
Candidates should have strong Python skills and experience in deploying LLM systems in production settings.
Production AI Agent Engineer - Scaled LLM Systems employer: Russell Tobin
At Russell Tobin, we pride ourselves on being an exceptional employer in the heart of Greater London, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through continuous learning opportunities and hands-on experience with cutting-edge AI technologies, making this role not just a job, but a pathway to a rewarding career in the rapidly evolving field of artificial intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Production AI Agent Engineer - Scaled LLM Systems
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech community, especially those who are already working on LLM systems. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to deploying LLM systems. This could be anything from GitHub repos to case studies. We want to see what you can do in action!
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding the latest trends in AI. We recommend doing mock interviews with friends or using online platforms to get comfortable with common questions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Production AI Agent Engineer - Scaled LLM Systems
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your Python expertise in your application. We want to see how you've used it in real-world projects, especially in deploying LLM systems. Don't hold back on the details!
Project Ownership is Key:Since this role involves owning projects from concept to deployment, share examples of past projects where you took the lead. We love seeing candidates who can drive a project forward and deliver results.
Collaboration is Crucial:We’re all about teamwork here at StudySmarter. Mention any experiences you have working with engineering teams or cross-functional groups. It shows us you can communicate and collaborate effectively.
Apply Through Our Website:To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Russell Tobin
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models (LLMs) before the interview. Be ready to discuss how you've deployed these systems in production settings and any challenges you've faced. This shows that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Python Skills
Since strong Python skills are a must for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your thought process while coding. Practising common algorithms or data structures in Python can really help you shine.
✨Project Ownership Stories
Be ready to share specific examples of projects you've owned from concept to deployment. Highlight your role, the challenges you faced, and how you collaborated with engineering teams. This will illustrate your ability to take initiative and work well with others.
✨Ask Insightful Questions
Prepare some thoughtful questions about the AI build project and the team dynamics. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your values. Plus, it gives you a chance to engage in a meaningful conversation.
