At a Glance
- Tasks: Design and own data infrastructure for AI at a fast-paced startup.
- Company: Dynamic Series-funded AI startup with a flat structure.
- Benefits: Competitive salary up to £130k, equity options, and high autonomy.
- Other info: Join a small, experienced team with direct access to founders.
- Why this job: Make a real impact by owning meaningful parts of the platform.
- Qualifications: 5+ years Python experience and hands-on database expertise.
The predicted salary is between 100000 - 130000 € per year.
We're hiring an AI Platform Engineer to own the data infrastructure at a Series-funded AI startup. This isn't a specialised role. You'll sit at the intersection of backend and AI engineering. You'll design and own the services and pipelines that move, transform, store and serve data across the product—including the AI-driven parts. That means: synchronisation across relational, document, vector, graph, object and blob stores. Making sync vs async, lambda vs delta architectural choices. Owning the platform for AI engineers who are shipping fast and need infrastructure to keep up.
What You'll Do
- Design, build and operate production Python services (REST/RPC and queue-based).
- Own the data backbone: ingestion, transformation, storage and retrieval.
- Make architecture trade-off decisions (latency, consistency, cost, operability) and own the consequences.
- Partner with product and AI engineers on clean, API-first service designs.
- Help your AI engineering team move from scrappy to scalable.
What You Need
- 5+ years production Python
- Hands-on experience with multiple database paradigms (relational + at least one of: vector, document, graph)
- Real infrastructure ownership—you've built and owned systems, not just contributed to them
- Comfort with microservice architecture and trade-off reasoning
- Nice to have: Event-based architecture (Kafka/NATS), infrastructure-as-code, gen-AI in production, product thinking.
About Us
- Small, experienced team. 13 people. No middle management—never will be. We move quickly, ship to production continuously, and obsess over product quality.
- Series-funded. Backed by top-tier investors. 300+ early users. Still in stealth.
Why Join
- Ownership: You own meaningful parts of the platform end-to-end. Short path from idea to production.
- Team: Small, experienced, high-energy. Direct access to founders. Low process, high autonomy.
- Infrastructure matters here: Data, AI and backend are all first-class concerns—not afterthoughts.
- Real compensation: Up to £130k salary (depending on experience) + equity up to 100% of salary in options.
Culture Note
We work flat. We don't micromanage. We hand you problems and you solve them. That means autonomy. It also means accountability. If you want a framework, process or middle management to hide behind—this isn't the place. If you want to own hard problems and move fast, get applying.
Artificial Intelligence Platform Engineer in London employer: Wave Group
Join a dynamic and innovative AI startup where you will have the opportunity to take ownership of critical data infrastructure in a flat, high-energy team environment. With direct access to founders and a culture that prioritises autonomy and accountability, you'll be empowered to make impactful architectural decisions while enjoying competitive compensation and equity options. This is a unique chance to work at the forefront of AI technology, contributing to a product that is already gaining traction with early users.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Python and data infrastructure. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss architecture trade-offs and your past experiences with different database paradigms. We want to see how you think!
✨Tip Number 4
Apply through our website! It’s the quickest way to get noticed. Make sure to tailor your application to highlight your ownership of systems and your ability to work in a fast-paced environment. We’re excited to see what you bring to the table!
We think you need these skills to ace Artificial Intelligence Platform Engineer in London
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and data infrastructure shine through. We want to see that you’re not just looking for a job, but that you’re genuinely excited about the impact of AI and how it can transform products.
Highlight Relevant Experience:Make sure to showcase your hands-on experience with Python and various database paradigms. We love seeing real ownership of systems, so don’t be shy about sharing specific projects where you’ve designed or built something impactful.
Be Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Use bullet points if necessary to make it easy for us to see your skills and experiences at a glance. Remember, we’re looking for someone who can communicate effectively.
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 shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Wave Group
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in Python and the various database paradigms mentioned in the job description. Brush up on your knowledge of relational, vector, document, and graph databases. Be ready to discuss how you've used these technologies in past projects and the architectural decisions you've made.
✨Showcase Your Ownership Experience
Prepare examples that highlight your experience in owning and building systems from the ground up. Talk about specific challenges you faced and how you overcame them. This will demonstrate your ability to take responsibility and make impactful decisions, which is crucial for this role.
✨Understand the Importance of Architecture Trade-offs
Be prepared to discuss architectural trade-offs you've made in previous roles. Think about scenarios where you had to balance latency, consistency, cost, and operability. This shows that you can think critically about infrastructure and understand the implications of your choices.
✨Emphasise Collaboration with AI Engineers
Since you'll be working closely with AI engineers, highlight your experience in partnering with cross-functional teams. Share examples of how you’ve contributed to API-first service designs and helped teams scale their operations. This will show that you can communicate effectively and work collaboratively in a fast-paced environment.
