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- Tasks: Build conversational AI workflows and develop RAG systems using cutting-edge technology.
- Company: Fast-growing tech company enhancing AI capabilities in Greater London.
- Benefits: Competitive salary, bonuses, and opportunities for professional growth.
- Other info: Exciting environment with potential for rapid career advancement.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Hands-on experience with LLMs, LangChain familiarity, and strong SQL skills.
The predicted salary is between 60000 - 80000 £ per year.
Oliver Bernard is seeking an AI Engineer in Greater London to work for a fast-growing tech company enhancing AI capabilities. The role involves building conversational AI workflows, implementing LLM tool use, and developing RAG systems.
Candidates should have:
- Hands-on experience with LLMs
- Familiarity with frameworks like LangChain
- Strong SQL skills
The position offers a competitive package plus bonuses.
AI Engineer: Conversational AI & RAG (London) employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer: Conversational AI & RAG (London)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, especially those working with conversational AI and LLMs. Attend meetups or webinars to connect with potential employers and show off your passion.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your hands-on experience with LLMs and frameworks like LangChain. Share projects that demonstrate your SQL prowess and how you've built conversational AI workflows.
✨Tip Number 3
Prepare for interviews by brushing up on common AI engineering questions. Be ready to discuss your experience with RAG systems and how you approach problem-solving in AI. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you're serious about joining our team and helps us get to know you better.
We think you need these skills to ace AI Engineer: Conversational AI & RAG (London)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your hands-on experience with LLMs and any frameworks like LangChain in your application. We want to see what you've done and how you can bring that expertise to our team!
Tailor Your Application: Don’t just send a generic CV! Tailor your application to the AI Engineer role by emphasising your SQL skills and any relevant projects. This helps us see how you fit into our vision.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your passion for conversational AI shines through without unnecessary fluff.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Oliver Bernard
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models (LLMs) before the interview. Be ready to discuss your hands-on experience with them, as well as any specific projects you've worked on that involved LLMs. This will show your potential employer that you're not just familiar with the theory but have practical skills to back it up.
✨Familiarise Yourself with LangChain
Since the job mentions frameworks like LangChain, take some time to understand its functionalities and how it can be applied in conversational AI workflows. You might even want to prepare a few examples of how you've used it or similar frameworks in past projects to demonstrate your expertise.
✨SQL Skills are Key
Strong SQL skills are essential for this role, so be prepared to showcase your ability to work with databases. Brush up on common SQL queries and be ready to discuss how you've used SQL in previous roles, especially in relation to data handling for AI systems.
✨Prepare Questions About RAG Systems
Research Retrieval-Augmented Generation (RAG) systems and come prepared with insightful questions about how the company implements these systems. This shows your genuine interest in the role and helps you gauge if the company's approach aligns with your own understanding and experience.