At a Glance
- Tasks: Help colleagues unlock AI's potential with hands-on projects and workshops.
- Company: Forward-thinking organisation embracing AI transformation.
- Benefits: Flexible work environment, opportunities for growth, and a chance to innovate.
- Other info: Join a dynamic team focused on responsible AI use and collaboration.
- Why this job: Make AI genuinely useful and impactful in everyday work.
- Qualifications: Experience with AI tools and a passion for helping others learn.
The predicted salary is between 63000 - 77000 £ per year.
Our client is investing in how AI can transform the way its people work.
They have already introduced Anthropic Claude across the organisation.
Now they want someone who can help colleagues unlock its potential.
This is not a traditional AI engineering role, nor is it about developing high-level AI strategies, it isabout making AI genuinely useful to people.
They are looking for someone who loves getting hands-on with Claude, experimenting with new capabilities and turning ideas into practical tools that make everyday work easier.
Just as importantly, you will enjoy sitting alongside colleagues, understanding their challenges and helping them discover how AI can support their work.
Some people will be complete beginners. Others will already be experimenting. You'll help both groups build their confidence and capabilities.
- What you'll be doing
- Building practical Claude Projects, Skills, agents and automated workflows that people can use in their everyday work.
- Working directly with colleagues to understand their challenges and identify where AI can genuinely help.
- Running engaging, hands-on workshops, demonstrations and one-to-one coaching sessions.
- Helping teams become confident and independent users of AI.
- Experimenting with connectors, integrations, MCP and lightweight automation.
- Developing reusable guides, templates and tools that can be shared across the organisation.
- Working alongside technology and product colleagues to turn promising ideas into useful solutions.
- Helping ensure AI is used responsibly, with appropriate consideration for data security and confidentiality.
- Who they are looking for
You might currently be working in AI enablement, generative AI consulting, AI adoption, learning and development, or a technical solutions role.
But your job title matters less than what you can actually do.
They are particularly interested in people who
Genuinely love Claude and generative AI.
You're naturally curious, constantly experimenting and probably building things in your spare time.
Can build, not just advise.
You've personally created useful AI tools, agents, Skills or workflows, ideally ones other people are now using.
Love helping others learn.
You're patient, approachable and can explain technology without unnecessary jargon.
Understand real-world adoption.
You know the difference between an impressive demonstration and something people actually use every day.
Have sound judgement.
You understand the importance of responsible AI, information security and knowing when human oversight matters.
You don't need to be a traditional software engineer, although technical curiosity and familiarity with integrations, APIs or simple scripting would be advantageous.
Equally, you don't need to have spent years working in AI.
They are more interested in what you have built, how you have helped others and how enthusiastically you approach the technology.
AI Enablement Specialist | Claude & Generative AI in London employer: Campbell Chamberlain
At Campbell Chamberlain, we pride ourselves on being an excellent employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through tailored professional development opportunities and a supportive environment that encourages strategic thinking and evidence-based decision-making. Located in a vibrant community, we offer unique advantages such as flexible working arrangements and a strong focus on social impact, making it a rewarding place for those looking to make a difference.
StudySmarter Expert Advice🤫
We think this is how you could land AI Enablement Specialist | Claude & Generative AI in London
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We think you need these skills to ace AI Enablement Specialist | Claude & Generative AI in London
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 Campbell Chamberlain, 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 Campbell Chamberlain. 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 Campbell Chamberlain
✨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 Campbell Chamberlain!
✨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.
