At a Glance
- Tasks: Design and build 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 focused on quality and innovation.
- Why this job: Own impactful projects and collaborate directly with founders in a vibrant team.
- 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 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. 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
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data engineering 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 you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and data infrastructure. We want to see how you’ve tackled real-world problems—this is your chance to shine!
✨Tip Number 3
Prepare for technical interviews by brushing up on your architecture trade-offs and database paradigms. We’re looking for someone who can think on their feet and make decisions under pressure, so practice articulating your thought process.
✨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 take the initiative to connect directly with us.
We think you need these skills to ace Artificial Intelligence Platform Engineer
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 genuinely care about the impact of your work in this exciting field.
Tailor Your Experience:Make sure to highlight your relevant experience with Python and various database paradigms. We’re looking for someone who has real ownership of systems, so share specific examples of projects where you've designed and built infrastructure.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see how your skills align with what we need for the AI Platform Engineer role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
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 building and owning systems. 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 trade-offs in architecture, such as latency vs consistency or cost vs operability. Think through scenarios where you had to make these decisions and be ready to explain your reasoning. This shows that you can think critically and strategically about infrastructure.
✨Emphasise Collaboration with AI Engineers
Since you'll be partnering with product and AI engineers, think of ways to illustrate your collaborative skills. Share experiences where you’ve worked closely with cross-functional teams to design clean, API-first services. This will show that you can communicate effectively and contribute to a team-oriented environment.
