At a Glance
- Tasks: Design and operationalise LLM-driven workflows for impactful decision-making.
- Company: Moonfire, a forward-thinking tech company in Greater London.
- Benefits: Hybrid working model, competitive salary, and opportunities for growth.
- Other info: Exciting role with a focus on innovation and collaboration.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Strong prompt engineering skills and experience with LLM agents required.
The predicted salary is between 60000 - 80000 £ per year.
Moonfire in Greater London is looking for an AI Engineer to design and operationalize LLM-driven workflows for generating decision-ready comparison reports. This role involves prompt engineering, context management, and integrating deterministic findings with LLM insights.
The position offers a hybrid working model and requires familiarity with Salesforce metadata. Candidates should possess strong prompt engineering skills and hands-on experience with LLM agents.
AI Engineer: Prompt & Context Architect for Graph-LLM employer: Moonfire
Moonfire is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. With a hybrid working model, employees enjoy flexibility while engaging in meaningful projects that drive their professional growth. The company prioritises employee development and provides unique opportunities to work with cutting-edge AI technologies, making it an ideal place for those looking to make a significant impact in the field.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer: Prompt & Context Architect for Graph-LLM
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech scene, especially those who work at Moonfire or similar companies. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your prompt engineering projects and LLM workflows. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for the interview by brushing up on Salesforce metadata and how it integrates with LLMs. Being knowledgeable about the tools they use will show you’re serious about the role and ready to hit the ground running.
✨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 take the initiative to connect directly with us.
We think you need these skills to ace AI Engineer: Prompt & Context Architect for Graph-LLM
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your prompt engineering skills and any hands-on experience with LLM agents in your application. We want to see how you can bring your expertise to the table!
Tailor Your Application:Don’t just send a generic CV! Tailor your application to reflect how your experience aligns with the role of AI Engineer at Moonfire. We love seeing candidates who take the time to connect their background with our needs.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your key points stand out without unnecessary fluff.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Moonfire
✨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 used them in past projects, especially in relation to prompt engineering and context management. This will show that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in designing workflows or integrating findings with LLM insights. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewer to see your thought process and problem-solving abilities.
✨Familiarise Yourself with Salesforce Metadata
Since the role requires familiarity with Salesforce metadata, do some research on how it integrates with AI workflows. Being able to discuss this knowledge during the interview will demonstrate your readiness for the role and your proactive approach to learning.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the company’s current projects or future plans regarding LLM-driven workflows. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals.
