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- Tasks: Design and deliver AI-powered applications using cutting-edge technologies.
- Company: Join a growing tech consultancy with a focus on practical AI solutions.
- Benefits: Competitive salary up to £115k, bonuses, and hybrid working.
- Other info: Work in a dynamic environment with opportunities for growth.
- Why this job: Lead impactful AI projects and collaborate with enterprise clients.
- Qualifications: Strong Python skills and experience with AI/LLM systems required.
The predicted salary is between 115000 - 115000 £ per year.
We’re partnered with a growing technology consultancy who are looking for a Lead AI Engineer to help deliver scalable, production-ready AI solutions for enterprise clients.
The role combines hands-on engineering, technical leadership, and client collaboration, with a strong focus on practical AI implementation rather than experimental POCs.
- Design and deliver AI-powered applications using LLMs and agent frameworks
- Integrate AI solutions into enterprise systems and digital products
- Support AI adoption and best practices across client environments
- Commercial experience deploying production AI/LLM systems
- Strong Python engineering background
- Experience with Azure or AWS AI services
- Knowledge of MLOps, Kubernetes, Docker, and vector databases
London hybrid working (Tue–Thu onsite)
Up to £115k + bonus
Lead AI Engineer - London (Hybrid) | Python, LLMs, Client-facing employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer - London (Hybrid) | Python, LLMs, Client-facing
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI or at consultancies. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Python and LLMs. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and client-facing skills. Be ready to discuss how you've implemented AI solutions in the past and how you can help clients adopt these technologies effectively.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Lead AI Engineer - London (Hybrid) | Python, LLMs, Client-facing
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python engineering background in your application. We want to see how you've used Python in real-world projects, especially in AI solutions. Don't hold back on those technical details!
Talk About Your Client Experience: Since this role is client-facing, share examples of how you've collaborated with clients in the past. We love to see how you’ve integrated AI solutions into their systems and helped them adopt best practices.
Demonstrate Your AI Knowledge: We’re looking for someone with commercial experience in deploying production AI/LLM systems. Make sure to mention any relevant projects or technologies you've worked with, like Azure, AWS, or MLOps.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we love seeing applications come in through our own channels!
How to prepare for a job interview at Oliver Bernard
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the specific AI technologies mentioned in the job description, like LLMs and MLOps. Brush up on your experience with Azure or AWS AI services, as you’ll likely be asked to discuss how you've used these tools in past projects.
✨Showcase Your Client-Facing Skills
Since this role involves client collaboration, prepare examples of how you've successfully communicated technical concepts to non-technical stakeholders. Think about times when you’ve led discussions or workshops that helped clients understand AI solutions.
✨Demonstrate Practical Implementation
Be ready to talk about real-world applications of AI you’ve worked on, especially those that went beyond experimental POCs. Highlight your experience in delivering scalable, production-ready solutions and how you tackled challenges during implementation.
✨Prepare for Technical Leadership Questions
As a Lead AI Engineer, you’ll need to show your leadership capabilities. Prepare to discuss your approach to mentoring junior engineers, leading projects, and fostering best practices in AI adoption within teams and client environments.