At a Glance
- Tasks: Build and evolve AI infrastructure software platforms using Python and Kubernetes.
- Company: Join a cutting-edge tech company focused on AI and infrastructure innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on solving real-world infrastructure challenges.
- Why this job: Make a real impact by building the backbone of AI technology at scale.
- Qualifications: Strong Python and Kubernetes skills, with experience in bare metal infrastructure.
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 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) in London employer: We Love Alfa
Join a forward-thinking company that prioritises innovation and collaboration, where as a Platform Engineer, you will be at the forefront of building cutting-edge AI infrastructure. Our dynamic work culture fosters continuous learning and growth, offering ample opportunities to enhance your skills in Python and Kubernetes while working alongside talented professionals. Located in a vibrant tech hub, we provide a stimulating environment that encourages creativity and problem-solving, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Engineer (AI Infrastructure) in London
✨Tip Number 1
Network, network, network! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. You never know who might be looking for a Platform Engineer like you!
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects or Kubernetes configurations. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each company. Research their tech stack and mention how your experience with bare metal infrastructure or GPU compute aligns with their needs when you reach out.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative to engage directly with us. Plus, it shows you're genuinely interested in being part of our team at StudySmarter.
We think you need these skills to ace Platform Engineer (AI Infrastructure) in London
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 scalable platform capabilities using Kubernetes. This will show us you can handle the complexities of our AI infrastructure.
Talk About Your Infrastructure Experience:We need someone who understands bare metal infrastructure, so include any relevant experience you have. Whether it’s working with Linux systems or networking, let us know how you’ve tackled real infrastructure problems through software.
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 this exciting role in building the future of AI infrastructure.
How to prepare for a job interview at We Love Alfa
✨Know Your Tech Inside Out
Make sure you brush up on your Python and Kubernetes skills. Be ready to discuss specific projects where you've built platform applications or worked with bare metal infrastructure. The more detailed your examples, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about real-world challenges you've faced in infrastructure and how you solved them through software. This role is all about building solutions, so highlight your practical engineering mindset.
✨Understand the Bigger Picture
Familiarise yourself with AI infrastructure and how it operates at scale. Be prepared to discuss how your work can impact reliability and performance across systems. Showing that you grasp the importance of your role will set you apart.
✨Collaborate and Communicate
This position involves working with various teams, so be ready to demonstrate your collaboration skills. Share examples of how you've successfully worked with product, security, and networking teams to build effective solutions.
