At a Glance
- Tasks: Design and build platform applications for large-scale AI infrastructure using Python and Kubernetes.
- Company: Join a cutting-edge tech company focused on AI infrastructure innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on solving real-world infrastructure challenges.
- Why this job: Make a real impact by building the backbone of AI technology.
- Qualifications: Strong Python and Kubernetes experience, with a focus on building scalable systems.
The predicted salary is between 60000 - 80000 € per year.
We are hiring a Platform Engineer to help build and evolve the software platform behind large scale AI infrastructure. This is a hands-on engineering role for someone who can write strong Python, work deeply with Kubernetes, design and build platform applications, and operate close to bare metal infrastructure. You will help build the systems that make GPU compute easier to provision, operate, secure and scale across AI infrastructure environments. This is not a generic DevOps role. We are not looking for someone who has only maintained pipelines, written Terraform or managed cloud services. We need someone who can build real platform software and understands the infrastructure it runs on.
What you will do:
- Design and build platform applications, APIs and services
- Write production grade Python for infrastructure and platform use cases
- Work with Kubernetes to build scalable platform capabilities
- Design and build Kubernetes operators and controllers across compute, storage and networking
- Build tooling that improves how bare metal and GPU infrastructure is provisioned, operated and monitored
- Translate operational pain points into scalable platform features
- Improve platform reliability, observability and performance
- Work across Linux, networking, storage and distributed systems
- Collaborate with product, security, infrastructure, networking and compute teams
- Help build the platform layer for AI infrastructure designed to operate at industrial scale
What we are looking for:
- Strong Python engineering experience
- Strong hands-on Kubernetes experience
- Experience designing and building applications, APIs, services or internal platform tooling
- Bare metal infrastructure experience
- Strong Linux systems experience
- Good understanding of networking, storage and distributed systems
- Experience building production grade systems with proper testing, CI/CD, code reviews and clean engineering standards
- A practical engineering mindset and the ability to solve real infrastructure problems through software
Preferred experience:
- Experience building Kubernetes operators, CRDs or controllers
- Exposure to GPU infrastructure, HPC or high performance compute
- Experience with Go or Rust
- Knowledge of confidential computing, including TEE, SEV, TDX or CoCo
- Experience with Ceph or distributed storage systems
- Familiarity with Prometheus, Grafana or OpenTelemetry
- Experience with BGP, RDMA or high performance networking
- Exposure to NVIDIA GPU infrastructure or bare metal cloud environments
Why this role matters:
AI infrastructure is constrained by the ability to deliver reliable compute at scale. This role sits in the platform layer that connects software engineering with real infrastructure. You will help build systems that run close to the metal, across Kubernetes, Linux, networking, storage and GPU compute. This is a role for someone who wants to build the infrastructure layer behind AI, not just operate tools around it.
Platform Engineer (AI Infrastructure) employer: We Love Alfa
Join a forward-thinking company that values innovation and technical excellence, where as a Platform Engineer, you will play a crucial role in shaping the future of AI infrastructure. Our collaborative work culture fosters creativity and problem-solving, offering ample opportunities for professional growth and development. Located in a vibrant tech hub, we provide a dynamic environment that encourages continuous learning and the chance to work with cutting-edge technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Engineer (AI Infrastructure)
✨Tip Number 1
Network like a pro! Attend meetups, conferences, or online webinars related to AI infrastructure and platform engineering. Engaging with industry professionals can open doors and give us insights into unadvertised job opportunities.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your projects, especially those involving Python, Kubernetes, or bare metal infrastructure. This gives potential employers a tangible look at what we can do and how we solve real problems.
✨Tip Number 3
Tailor your approach! When reaching out to companies, including us at StudySmarter, make sure to highlight your hands-on experience with the specific technologies mentioned in the job description. Personalising your message can make a huge difference.
✨Tip Number 4
Don’t just apply, engage! When you find a role that excites you, apply through our website and follow up with a friendly email. Express your enthusiasm for the position and mention any relevant projects or experiences that align with the job requirements.
We think you need these skills to ace Platform Engineer (AI Infrastructure)
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your strong Python engineering experience in your application. We want to see examples of how you've used Python to build real platform software, so don’t hold back on sharing your projects or contributions!
Kubernetes is Key:Since we’re looking for someone with hands-on Kubernetes experience, be sure to detail any projects where you’ve designed and built applications or services using Kubernetes. This will show us that you can handle the scale and complexity of our AI infrastructure.
Talk About Your Infrastructure Experience:We need someone who understands bare metal infrastructure and has a solid grasp of Linux systems. In your application, share specific instances where you've tackled infrastructure challenges and how you approached them. This will help us see your practical engineering mindset.
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 what we do at StudySmarter.
How to prepare for a job interview at We Love Alfa
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your past projects and how you've used Python to solve real-world problems, especially in infrastructure contexts. They’ll want to see that you can write production-grade code, so be prepared for some coding challenges.
✨Get Hands-On with Kubernetes
Since this role heavily involves Kubernetes, it’s crucial to demonstrate your hands-on experience. Familiarise yourself with building scalable platform capabilities and designing Kubernetes operators. You might even want to prepare a few examples of how you've tackled challenges using Kubernetes in previous roles.
✨Understand Bare Metal Infrastructure
This isn’t just about cloud services; they’re looking for someone who understands bare metal infrastructure. Brush up on your knowledge of how to provision and operate hardware directly. Be ready to discuss any relevant experiences you have with bare metal setups and how you’ve improved their performance.
✨Show Your Problem-Solving Skills
They want a practical engineer who can translate operational pain points into scalable solutions. Think of specific instances where you identified a problem and implemented a successful solution. Be prepared to explain your thought process and the impact of your work on the overall system reliability and performance.
