At a Glance
- Tasks: Design and build cloud infrastructure for AI and ML models at scale.
- Company: Leading UK fintech with a focus on innovative AI solutions.
- Benefits: Up to £115,000 salary, private medical, share schemes, and flexible working.
- Other info: Join a dynamic team with ownership over critical AI projects.
- Why this job: Shape foundational AI infrastructure and make a real impact in fintech.
- Qualifications: Strong platform engineering background, Kubernetes experience, and LLM application knowledge.
The predicted salary is between 115000 - 115000 £ per year.
We're partnering with a leading UK fintech on a senior hire inside their AI and Machine Learning team.
This is a platform-first role. The team is building the foundational AI infrastructure the rest of the business will run on and right now, that's the priority. Think LLM API gateway, model standardisation, cost dashboards, monitoring, quota management, and internal agent tooling. The kind of work that matters more the bigger the organisation gets.
What you'll be working on:
- Designing and building cloud infrastructure for hosting and serving ML and GenAI models at scale
- Owning the LLM gateway — standardising model usage, monitoring, cost control, and quotas across the business
- Building frameworks and tooling that make AI development consistent and governable
- Integrating and evaluating third-party AI tools and agent frameworks
- Shaping Responsible AI practices into the platform from day one
What they're looking for:
- Strong platform and cloud engineering background — AWS preferred, but open on background if the fundamentals are there
- Solid Kubernetes experience (around 80% of the role), with some serverless on top
- Hands-on experience with LLM-based applications — RAG, vector databases, agent frameworks
- Product-minded and commercially aware — this isn't a pure SRE or ops profile
- Comfortable working across Data Science, Engineering, Product, and Security stakeholders
Why it's worth a look:
- Joining at the right time — the platform is being built now, and you'll shape how it evolves
- Real ownership over foundational infrastructure the whole business will depend on
- Fintech scale with public company stability — restless energy, serious backing
- Up to £115,000 + strong benefits including private medical, share schemes, learning allowance, and flexible working
- Hybrid, 2 days in the London office
If you're a platform or cloud engineer looking to move into the AI infrastructure space or already there and want to go deeper this is a strong move.
Senior AI Platform Engineer in London employer: Wave Group
As a leading UK fintech, we offer an exciting opportunity for a Senior AI Platform Engineer to join our dynamic team in London. With a strong focus on innovation and collaboration, our hybrid work culture promotes flexibility while providing robust benefits such as private medical insurance, share schemes, and a learning allowance. You'll have the chance to take ownership of foundational AI infrastructure that will shape the future of our business, all within a supportive environment that prioritises employee growth and development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech and AI space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational chats. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to cloud infrastructure and AI. This is your chance to demonstrate your hands-on experience with LLM applications and Kubernetes. Let your work speak for itself!
✨Tip Number 3
Prepare for those interviews! Research the company’s AI initiatives and think about how your background aligns with their needs. Be ready to discuss your experience with AWS, Kubernetes, and any relevant tools. Confidence is key, so practice makes perfect!
✨Tip Number 4
Apply through our website! We’ve got a streamlined process that makes it easy for you to showcase your skills. Plus, it shows you’re genuinely interested in joining our team. Don’t miss out on this opportunity to shape the future of AI infrastructure!
We think you need these skills to ace Senior AI Platform Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior AI Platform Engineer role. Highlight your platform and cloud engineering background, especially any experience with AWS and Kubernetes, as these are key for us.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI infrastructure. Share specific examples of your work with LLM-based applications or any frameworks you've built, so we can see how you fit into our vision.
Showcase Your Collaboration Skills:Since this role involves working across various teams, mention any past experiences where you've collaborated with Data Science, Engineering, Product, or Security stakeholders. We want to know how you can contribute to our team dynamic!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our growing AI and Machine Learning team.
How to prepare for a job interview at Wave Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS and Kubernetes. Brush up on your experience with LLM-based applications and be ready to discuss specific projects where you've implemented these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, particularly around building cloud infrastructure or standardising model usage. Use examples that highlight your ability to integrate third-party tools and frameworks effectively.
✨Understand the Business Impact
This role isn’t just about tech; it’s about how your work impacts the business. Be prepared to talk about how your engineering decisions can drive commercial success and improve operational efficiency within a fintech context.
✨Engage with Stakeholders
Since this role involves working across various teams, think about how you’ve collaborated with Data Science, Engineering, Product, and Security stakeholders in the past. Be ready to share examples of how you’ve communicated complex ideas to non-technical team members.
