Cloud Data & AI Engineer in London

Cloud Data & AI Engineer in London

London Full-Time 63000 - 77000 £ / year (est.) Hybrid
C

At a Glance

  • Tasks: Design and develop scalable cloud data platforms and AI solutions.
  • Company: Join Capgemini, a global leader in tech transformation and innovation.
  • Benefits: Enjoy competitive salary, wellbeing support, and endless learning opportunities.
  • Other info: Be part of a diverse team committed to ethical business practices.
  • Why this job: Make a real impact with cutting-edge AI and cloud technologies.
  • Qualifications: Experience in Cloud Data Engineering and MLOps required.

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

We are seeking a highly skilled Cloud Data & AI Engineer with strong expertise in MLOPS, Cloud Data Engineering, Artificial Intelligence, and the Insurance domain. The successful candidate will be responsible for designing, developing, and deploying scalable cloud-based data platforms and AI solutions, including Generative AI and Large Language Model (LLM) use cases. The role requires close collaboration with business, data, and technology teams to deliver reliable, secure, and high-performing data products that drive business value.

Your Role:

  • Design, build, and maintain scalable, secure, and high-performance data platforms on cloud environments.
  • Develop and optimize data pipelines for batch and real-time data processing.
  • Develop, deploy, and optimize AI/ML solutions including Generative AI and LLM-based applications.
  • Integrate AI services into cloud-native data platforms.
  • Utilize MLflow for experiment tracking, model registry, versioning, and deployment.
  • Establish and maintain MLOps practices for model governance and reproducibility.

Your Skills:

  • Hands-on experience in Cloud Data Engineering including designing and implementing scalable data platforms on cloud environments with expertise in leveraging and optimizing LLM-based use cases.
  • Strong understanding of Insurance domain data models, business processes, and data governance requirements.
  • Experience with MLflow for machine learning lifecycle management including experiment tracking, model registry, and deployment.
  • Proficiency in unit testing, version control (Git), CI/CD pipelines, and production deployment of cloud-based data and AI solutions ensuring reliability, scalability, and maintainability.

We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role.

Make It Real (what does it mean for you): You’d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce as a critical component for us to achieve our organisational ambitions. To help support wellbeing, we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy. You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from think tanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications, and much more.

You will be joining one of the World’s Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.

Why you should consider Capgemini: Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you’ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs, and industry experts. We find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.

About Capgemini: Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology, and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering, and business operations.

Cloud Data & AI Engineer in London employer: Capgemini

Capgemini is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a hybrid working model, employees enjoy the flexibility of blending office, client site, and home working, while also benefiting from extensive growth opportunities and professional development within the Capital Markets sector. Join us to be part of a team that values governance excellence and empowers you to make a meaningful impact in complex programme environments.

C

Contact Details:

Capgemini Recruitment Team

StudySmarter Expert Advice🤫

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

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Capgemini!

✨Show Off Your Projects

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 Cloud Data & AI Engineer at Capgemini.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Capgemini.

✨Apply Directly through Our Website

When you find a suitable opening like Cloud Data & AI Engineer at Capgemini, 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 Cloud Data & AI Engineer in London

MLOPS
Cloud Data Engineering
Artificial Intelligence
Generative AI
Large Language Model (LLM)
Data Pipeline Development
MLflow

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Capgemini, 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 Capgemini. 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 Capgemini

✨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!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨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 Capgemini!

✨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.