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- Tasks: Lead a team to develop AI solutions that transform the insurance industry.
- Company: Top UK insurance firm focused on innovation and technology.
- Benefits: Flexible hybrid work, competitive salary, and opportunities for professional growth.
- Why this job: Shape the future of insurance with cutting-edge AI technology.
- Qualifications: Proven experience in AI engineering and leadership skills.
- Other info: Join a dynamic team and make a real impact in a thriving industry.
The predicted salary is between 54000 - 84000 £ per year.
A leading insurance company in the UK is seeking a Lead AI Engineer to spearhead AI-powered solutions that shape the future of insurance. The successful candidate will lead a diverse team of AI Engineers and be responsible for setting technical direction, delivering impactful projects, and mentoring team members. This hybrid role allows for a flexible work environment while making a significant contribution to the company's AI strategy.
Lead AI Engineer - Drive Strategy & Impact (Hybrid) employer: Ageas UK
Contact Detail:
Ageas UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer - Drive Strategy & Impact (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to current employees at the company through LinkedIn or industry events. A friendly chat can give us insights into the company culture and might even lead to a referral.
✨Tip Number 2
Showcase your skills! Prepare a portfolio of your AI projects that demonstrate your technical prowess and leadership abilities. This will help us stand out during interviews and show how we can drive strategy and impact.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or use online platforms to refine our responses. Focus on articulating how our experience aligns with the company's goals in AI-powered solutions.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets noticed. Plus, it shows our enthusiasm for the role and the company, which can make a great first impression.
We think you need these skills to ace Lead AI Engineer - Drive Strategy & Impact (Hybrid)
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI shine through! We want to see how you can drive strategy and impact in the insurance sector. Share any relevant projects or experiences that highlight your passion and expertise.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this role. We’re looking for someone who can lead a diverse team and set technical direction, so highlight your leadership experience and any successful projects you've managed in the past.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that are easy to read. Use bullet points where necessary to make your achievements stand out and ensure we can quickly see your qualifications.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Ageas UK
✨Know Your AI Stuff
Make sure you brush up on the latest trends and technologies in AI, especially those relevant to the insurance sector. Be ready to discuss how you've applied AI solutions in past projects and how they can impact the future of insurance.
✨Show Leadership Skills
As a Lead AI Engineer, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've successfully guided teams in the past, tackled challenges, and fostered collaboration among diverse team members.
✨Understand the Company’s Vision
Research the insurance company’s current AI initiatives and their overall strategy. This will help you align your answers with their goals and show that you're genuinely interested in contributing to their mission.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving skills and knowledge of AI frameworks. Practise coding challenges or case studies that are relevant to the role, so you can showcase your expertise confidently.
