At a Glance
- Tasks: Build and ship innovative GenAI applications from scratch in a dynamic fintech environment.
- Company: Fast-moving fintech company with a collaborative, high-ownership culture.
- Benefits: Competitive salary up to £115k, bonuses, and hybrid work model.
- Other info: Opportunity for both Mid and Senior levels with excellent career growth.
- Why this job: Join a small team and make a real impact on cutting-edge AI products.
- Qualifications: Strong Python skills and experience with GenAI or LLMs required.
The predicted salary is between 115000 - 115000 £ per year.
A high-impact AI Engineer hire inside a fintech business building production-grade AI products from the ground up. This is a rare opportunity to join a small, fast-moving AI team with real ownership over greenfield products — shipping GenAI applications that directly influence how a market-leading lending platform operates.
The Opportunity
Join a cross-functional AI and Machine Learning team operating like a startup within an established, publicly listed fintech business. Projects are 80–90% greenfield. You'll bridge the gap between data science POCs and production-grade systems, owning AI products from experimentation through to live deployment. This is a role for engineers who want to build, ship and own — not just advise.
About the Role
- You'll be building and shipping GenAI applications end-to-end into production.
- Own how AI systems integrate with existing product infrastructure.
- Handle real-world failure states and production engineering decisions.
- Collaborate closely with data scientists, platform engineers and PMs.
- Contribute to best practices for AI product development across the business.
- Mentor teammates and stay current in a fast-moving space.
You'll work exclusively in Python with FastAPI. Strong software engineering fundamentals matter here as much as AI experience.
What You'll Be Working On
- Website chatbot and conversational AI products.
- Internal AI tooling and automation.
- Document processing pipelines.
- RAG pipelines, LLM integrations and agent frameworks.
- Taking POCs to production-grade systems at scale.
Skills and Experience
- Strong Python engineering fundamentals — this is an engineering role first.
- Hands-on experience with GenAI, LLMs, RAG or agent frameworks.
- Product mindset with comfort owning end-to-end delivery.
- Actively using AI tools in your own workflow (Claude, Copilot etc.).
- Fast-learning and motivated to move with a rapidly evolving space.
Nice to have:
- Full-stack experience (JavaScript/TypeScript).
- Experience taking AI products from POC to production commercially.
Location: London – Hybrid (min. 2 days/week)
Compensation: Up to £115k + bonus
Team: Small, collaborative, fast-moving — high ownership culture.
Stage: Greenfield AI products inside an established, scaled business.
We're hiring for both Mid and Senior levels — if you're genuinely building in AI and want real ownership over products that matter, this is worth a conversation.
Engineer (M/V) employer: Wave Talent
Join a dynamic fintech company that champions innovation and ownership, offering AI Engineers the chance to work on greenfield projects that shape the future of lending. With a collaborative culture and a commitment to employee growth, you'll thrive in a hybrid environment that values your contributions and encourages continuous learning. Enjoy competitive compensation and the opportunity to make a real impact in a fast-paced, high-impact team.
StudySmarter Expert Advice🤫
We think this is how you could land Engineer (M/V)
✨Tip Number 1
Network like a pro! Reach out to people in the fintech and AI space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI or Python. We want to see what you can do, so make sure to highlight any greenfield projects you've worked on.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python fundamentals and AI concepts. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Engineer (M/V)
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI shine through! Share specific projects or experiences that highlight your journey in the AI space. We want to see how you've engaged with AI tools and technologies in your own workflow.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for this role. Highlight your Python engineering skills and any experience with GenAI or LLMs. We love seeing candidates who take the time to align their application with what we’re looking for!
Be Clear About Your Ownership Experience:In your application, emphasise instances where you've taken ownership of projects from start to finish. We’re all about real ownership here at StudySmarter, so show us how you’ve built and shipped products in the past!
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 gives you a chance to explore more about our team and culture!
How to prepare for a job interview at Wave Talent
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the specific frameworks mentioned in the job description, like FastAPI. Brush up on your understanding of GenAI, LLMs, and RAG pipelines. Being able to discuss your hands-on experience with these technologies will show that you’re not just a theorist but someone who can get things done.
✨Showcase Your Ownership Mindset
This role is all about taking charge of projects from start to finish. Prepare examples from your past work where you’ve owned a project or product. Highlight how you’ve navigated challenges and made decisions that led to successful outcomes. This will demonstrate that you’re ready for the high-impact environment they’re offering.
✨Prepare for Real-World Scenarios
Expect questions about handling production failures and engineering decisions. Think of scenarios where you had to troubleshoot or pivot quickly. Being able to articulate your thought process in these situations will show that you’re equipped to handle the pressures of a fast-moving team.
✨Collaborate and Communicate
Since this role involves working closely with data scientists and platform engineers, be ready to discuss how you’ve collaborated in the past. Share experiences where effective communication led to better outcomes. This will highlight your ability to fit into their small, collaborative team culture.
