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Generative AI Engineer

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AI Engineer – Internal AI Applications
Location: London
Working Model: Hybrid working available
Salary: £80,000 – £90,000 + benefits and bonus
Note: Sponsorship is not available
We're looking for an AI Engineer who loves building great software for people who actually want to use it.
Our client is investing heavily in AI, but this isn't a research role and it's not about building AI for the sake of it. The team is focused on creating high-quality internal applications that genuinely improve how people work - taking ideas from an early concept through to something people use every day.
You'll work across the full product and engineering lifecycle: understanding the problem, working with users, designing the solution, building it, testing it, launching it and then continuously improving it.
AI is at the heart of what the team is doing, with applications incorporating LLMs, RAG, agents, automation and other emerging technologies. But the focus is ultimately on building useful, reliable and well-engineered applications, rather than simply experimenting with models.
What you'll be doing
- Involved in a mixture of new product development and improving existing applications
- Build and develop AI-powered internal applications from concept through to production
- Work closely with users and stakeholders to understand what they're actually trying to achieve and turn that into practical technology
- Design intuitive, reliable applications that make complex tasks simpler and improve the user experience
- Develop backend services, APIs and AI workflows using Python and modern software engineering practices
- Build user-facing experiences using React and JavaScript/TypeScript
- Work with LLMs and technologies such as RAG, agents, tool calling and retrieval to create genuinely useful AI capabilities
- Prototype quickly, test ideas with users and iterate based on feedback
- Think about the things that make an application production-ready — performance, security, reliability, monitoring, testing and maintainability
- Integrate AI applications with existing business systems, data and APIs
- Work with the wider engineering and technology teams to deploy and support applications in production
- Keep up with developments in AI and identify where new technology can genuinely improve an existing product or create something new
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What we're looking for


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We're particularly interested in engineers who enjoy building things.
You don't need to be an AI researcher. You do need to be a strong software engineer who understands how modern AI can be used to build better applications.
You'll ideally have:
- Strong commercial experience building production-quality software applications
- Strong Python development skills
- Experience with React and JavaScript/TypeScript or similar modern frontend technologies
- Practical experience building applications using LLMs and Generative AI
- A good understanding of concepts such as RAG, embeddings, agents, tool calling and prompt engineering
- Experience taking ideas or prototypes through to production
- Good understanding of APIs, databases, cloud platforms and modern software engineering principles
- An interest in product and user experience, not just the underlying technology
- The ability to take a loosely defined problem and work out what a good technical solution looks like
- Strong communication skills and the ability to work directly with both technical and non-technical stakeholders
- A genuine curiosity about AI and a desire to keep learning as the technology develops
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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