At a Glance
- Tasks: Design and maintain infrastructure for scalable AI inference workloads.
- Company: Join Gcore, a global leader in AI-driven infrastructure solutions.
- Benefits: Enjoy competitive pay, flexible hours, remote work, and extra vacation days.
- Other info: Collaborate with top tech partners and enjoy a dynamic work environment.
- Why this job: Make an impact on cutting-edge AI technology that connects the world.
- Qualifications: Experience with Kubernetes, Linux, and automation tools like Python or Go.
The predicted salary is between 60000 - 80000 £ per year.
This position is available only under an employment (labor) agreement. The world’s digital experiences run on something invisible: the infrastructure and software that keep them fast, reliable, and secure. At Gcore, you’ll help design and deliver that foundation for an AI-driven world. We’re a global provider of infrastructure and software solutions for AI, cloud, network, and security, powering everything from real-time communication and streaming to enterprise AI and secure web applications. With 210+ edge locations, 50+ cloud regions, and thousands of GPUs, your work here can reach users and businesses across the globe. You’ll collaborate with leading technology partners such as Intel, NVIDIA, Dell, and Equinix, and work on platforms that power digital products used around the world. Our vision is simple: to connect the world to AI, anywhere, anytime. Want to work on technology that goes beyond a single product or industry? Join a global team of 550+ professionals building infrastructure and software that supports the entire digital ecosystem.
We are looking for a talented DevOps Engineer to join our AI Inference Operations Team. As a DevOps Engineer, you will be responsible for designing, deploying, and maintaining infrastructure and services that enable scalable and secure AI inference workloads on-premises.
What You Will Do
- Design, develop, and maintain infrastructure for AI inference workloads, including GPU scheduling, model deployment pipelines, and data access patterns in on‑prem environments.
- Build and manage monitoring and observability tools for AI inference platforms, including dashboards, alerts, and runbooks for model health and system performance.
- Collaborate with ML engineers and platform teams to design system architecture for AI workloads, integrate inference runtimes, and test performance at scale.
What We’re Looking For
- Strong understanding of Kubernetes architecture, including CNI, CSI, operators, ingress/gateway, and control plane components.
- Hands‑on experience operating and troubleshooting production Kubernetes clusters.
- Strong Linux and networking troubleshooting skills, including DNS, routing, firewalling, TLS, MTU, connectivity and performance issues.
- Ability to develop automation and operational tooling using Python, Go, or Bash.
- Experience with Terraform, Ansible, or similar IaC/configuration management tools.
- Experience with VictoriaMetrics/Grafana or similar monitoring, alerting, and troubleshooting tools.
- Strong experience with Git‑based workflows and CI/CD pipelines.
Preferred Qualifications
- Familiarity with Cluster API or similar Kubernetes cluster lifecycle management technologies.
- Hands‑on operation or administration of Slurm clusters.
- Knowledge of Argo CD, GitOps workflows, Helm, or Helmfile.
- Background working with managed platforms, PaaS, or cloud services.
- Exposure to bare metal, GPU, HPC, or other high‑performance computing environments.
Nice to Have
- Familiarity with the NVIDIA GPU stack, RDMA/InfiniBand, or high‑performance networking.
- Knowledge of OpenStack or similar cloud infrastructure platforms.
- Hands‑on experience developing Kubernetes operators or controllers.
Benefits
At Gcore, we want you to do your best work and enjoy the journey. Our benefits are designed to support your growth, well‑being, and life beyond work:
- Competitive compensation.
- Flexible working hours and hybrid or remote options, depending on your role.
- Work from anywhere in the world for up to 45 days per year.
- Private medical insurance for you and your family.
- Extra paid vacation and sick leave days.
- Support for life’s important moments and celebrations.
- Language courses to help you connect and grow.
- Modern, welcoming offices with snacks, drinks, and entertainment.
- Team sports and social activities.
*Benefits may vary depending on your location.
Equal Opportunity Employer
We provide equal opportunity to all applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity, gender expression, national origin, disability, or any other legally protected characteristics.
StudySmarter Expert Advice🤫
We think this is how you could land DevOps Engineer (AI Inference)
✨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 Gcore 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 Gcore.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Gcore.
✨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 Gcore 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 DevOps Engineer (AI Inference)
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 Gcore.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Gcore 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 Gcore
✨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 Gcore 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.
