At a Glance
- Tasks: Build and maintain a cutting-edge LLM inference platform using Go and Kubernetes.
- Company: Join Verda, a global AI cloud company making a positive impact.
- Benefits: Competitive cash and equity compensation, healthcare, and wellbeing perks.
- Other info: Work remotely in Europe or from our offices in Helsinki or London.
- Why this job: Be part of an innovative team shaping the future of AI infrastructure.
- Qualifications: 4+ years in Go, Kubernetes expertise, and strong SQL skills required.
The predicted salary is between 72000 - 88000 £ per year.
At Verda, we're building a full-stack AI cloud, covering everything from data centers and hardware to our own cloud platform that the world's leading AI teams use to do serious AI work.
We strive to make a positive mark on the world through the infrastructure we build and give leading teams a service they can truly depend on.
Headquartered in Helsinki, we operate globally with offices in London and San Francisco.
Join Verda while it's still being built - not once it's finished.
About The Role
We run a multi-tenant LLM inference platform: customers send requests to an Open AI-compatible gateway, and we handle routing, tenancy, access control, usage metering and billing on top of our own GPU fleet.
You would own backend services and the Kubernetes platform they run on.
This is not a role where infrastructure is someone else's problem, you write the Go service, the Helm chart, the network policy and the runbook, and you are the one who verifies it in production.
- We are moving deliberately toward a
- Kubernetes-native architecture
: less imperative tooling and hand-run scripts, more declarative APIs, custom resources and controllers that reconcile state.
If you have wanted to build operators and control planes rather than consume them, that is the direction of this role.
- Your Responsibilities
- Backend services in Go - the platform API, the customer-facing usage API, the metering and billing pipeline. Small, focused services with real correctness requirements.
- Kubernetes-native platform work - Git Ops deployment, custom resources and controllers, progressive rollout, network policy, secret and certificate management.
Moving what is currently scripted into something that reconciles.
- Multi-tenancy and access control - tenant provisioning, per-project model access, credential handling across environments.
- Usage metering and billing correctness - a pipeline that turns raw requests into per-tenant token accounting, plus the reconciliation that proves what we bill matches what actually happened.
This is money, and it has to be right.
- Observability - logs, metrics and traces that answer questions during an incident rather than after it.
- Your key competencies
- 4+ years of experience
- Strong Go.
You have shipped and maintained production Go services, and you are comfortable with concurrency, context propagation and error handling that fails loudly instead of silently.
- Real Kubernetes depth.
Not just kubectl apply.
You understand the control loop, know why a pod is not ready without guessing, and have written Helm charts, network policies and RBAC that you then had to debug.
- SQL and relational data modelling. Postgre SQL specifically. You can reason about transactions, indexes, migration safety.
- You verify your work. You do not report something as working because it deployed and the health check is green. You go and prove it, and you say plainly what you did not test.
- Clear written English. Design notes, runbooks, incident write-ups. Much of our engineering context lives in writing.
- Nice to have
- Building Kubernetes operators / controllers (controller-runtime, CRDs, kubebuilder, Operator SDK)
- Git Ops at scale - Argo CD or Flux, Application Sets, multi-cluster
- LLM serving internals - v LLM, SGLang, Tensor RT-LLM, KServe, or similar; GPU scheduling, batching, KV cache behaviour
- Distributed messaging (NATS, Kafka) and event-driven pipelines
- Traefik or Envoy/Istio at the ingress layer
- Time-series and log stores (Victoria Metrics/Victoria Logs, Prometheus, Click House)
- Frontend competence (React + Type Script) - our operator console is ours to maintain, and being able to fix it end to end is valuable
- Billing, metering or payments systems, or anything else where being wrong is expensive
- Python, for the gateway extension layer
- Why Verda
- Cash and equity compensation along with various fringe benefits (healthcare, lunch, wellbeing, and more).
- Profitable operations with rapid, sustained growth.
- 40+ nationalities, with 6 different ones on the management team.
- A real chance to make an impact and work alongside world class engineers, researchers, and partners across the global AI ecosystem.
- Practicalities
- Work mode: Based in Helsinki / London or remote in Europe
- Level: Senior
- Employment type: Full time and permanent
- #J-18808-Ljbffr
Platform Engineer - LLM Inference Infrastructure in London employer: Verda
Verda is an exceptional employer that fosters a vibrant multicultural work environment, making it an ideal place for a Technical Account Manager to thrive. With competitive cash and equity compensation, along with opportunities to collaborate with innovative AI companies, employees are encouraged to grow and develop their skills while managing impactful technical relationships. The company's commitment to enhancing customer experience and providing robust support ensures that team members feel valued and empowered in their roles.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Engineer - LLM Inference Infrastructure in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Verda or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Verda.
✨Tap into Online Developer Communities
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✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Verda that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Platform Engineer - LLM Inference Infrastructure in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Verda.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Verda and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Verda
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Verda uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
