AI Engineer in London

AI Engineer in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Hanson Lee

At a Glance

  • Tasks: Design and deploy cutting-edge AI applications that transform the insurance industry.
  • Company: Leading London Market insurer investing in innovative AI solutions.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on responsible AI practices and governance.
  • Why this job: Make a real impact on enterprise-scale AI projects in a collaborative environment.
  • Qualifications: Experience with Azure OpenAI, LLMs, and cloud-native development.

The predicted salary is between 63000 - 77000 £ per year.

We're partnering with a leading London Market insurer that is investing heavily in Generative AI to transform underwriting, claims, and operational processes.

They're looking for an experienced AI Engineer to join a growing technology team and play a key role in designing and delivering enterprise AI solutions.

This is an opportunity to work on cutting-edge AI initiatives in a highly collaborative environment where your work will have a direct impact on the business.

Key Responsibilities

  • Design, build and deploy production-ready AI applications using Large Language Models (LLMs).
  • Develop Retrieval Augmented Generation (RAG) solutions and AI agents.
  • Integrate AI capabilities with enterprise systems and internal data platforms.
  • Build secure, scalable APIs and services using Python.
  • Work closely with business stakeholders to identify and deliver high-value AI use cases.
  • Evaluate and optimise model performance, accuracy and reliability.
  • Ensure solutions meet governance, security and regulatory requirements.

Keen to speak with AI Engineers who have experience in

  • Azure Open AI and the Azure AI ecosystem
  • Lang Chain, Lang Graph, Llama Index or similar AI frameworks
  • Prompt engineering and LLM optimisation
  • Vector databases and semantic search
  • REST APIs and cloud-native development
  • Git, CI/CD and containerisation (Docker/Kubernetes)
  • AI governance, security and responsible AI practices

Highly desirable

  • Experience within the London Market, Lloyd's or the wider insurance sector.
  • Knowledge of underwriting, claims or insurance operations.
  • Exposure to Microsoft Fabric, Databricks or Azure AI Search.

If you're an experienced AI Engineer looking to work on meaningful, enterprise-scale AI projects within the London Market, we'd love to hear from you.

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AI Engineer in London employer: Hanson Lee

Hanson Lee offers a dynamic and supportive work environment in the heart of London, making it an excellent employer for those looking to grow in the customer success field. With a strong emphasis on employee development, you will have access to mentorship from experienced leaders and opportunities to influence product direction while working with a diverse portfolio of clients. The hybrid work model promotes a healthy work-life balance, ensuring that you can thrive both personally and professionally.

Hanson Lee

Contact Details:

Hanson Lee Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Engineer in London

Get Involved in Data Science Meetups

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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Engineer at Hanson Lee.

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Apply Directly through Our Website

When you find a suitable opening like AI Engineer at Hanson Lee, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI Engineer in London

Large Language Models (LLMs)
Retrieval Augmented Generation (RAG)
AI agents development
Integration with enterprise systems
Python programming
API development
Model performance evaluation

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at Hanson Lee, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Hanson Lee. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Hanson Lee

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Hanson Lee!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.