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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Infrastructure Operations Bootcamp Instructor - **Company:** WeCloudData - **Location:** UK (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Nvidia CUDA, Data Centers, Linux, DevOps, Monitoring of Systems, Image Management, Python (Programming Language), Laboratory Information Management Systems, Linux System Administration, Machine Learning, Networking Basics, Reliability Engineering, Prometheus, Shell Script, Software Deployment, AI Infrastructure, Data Logging, Scripting, Graphics Processing Unit (GPU), Google Cloud, Autoscaling, Large Language Models, Grafana, Containerization, AI Platforms, Kubernetes, Machine Learning Operations, Nim (Programming Language), Docker - **Published:** June 4, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=33f31e7bcd4f861e ## About the Role Do you have experience in Python?, Do you have a Master's degree?, 5+ years of experience in one or more of the following: * Platform Engineering * Cloud Engineering * Site Reliability Engineering (SRE) * MLOps * AI Platform Operations * Infrastructure Engineering * DevOps Engineering Preferred * 2+ years supporting AI or machine learning workloads in production Technical Expertise - Linux - Strong hands-on experience with: * Linux administration * Shell scripting * Process management * Networking fundamentals * System troubleshooting - Containers - Strong experience with: * Docker * Container image management * Containerized application deployment - Kubernetes - Practical experience with: * Pods * Deployments * Services * Ingress * Autoscaling * Helm * Monitoring Kubernetes workloads - Cloud Platforms - Experience with one or more: * AWS * Azure * Google Cloud * Alibaba Cloud - Monitoring & Observability - Experience with: * Prometheus * Grafana * Logging platforms * Alerting systems * Infrastructure monitoring AI Infrastructure Knowledge - Must understand: * Training vs inference workloads * AI deployment architectures * Model serving concepts * GPU utilization concepts * AI workload bottlenecks * Throughput and latency metrics * AI platform operations - The instructor does not need to be an AI researcher but should be comfortable deploying and operating AI workloads. Preferred Qualifications GPU & AI Infrastructure - Experience with: * NVIDIA GPUs * CUDA ecosystem * GPU monitoring tools * GPU scheduling concepts * Multi-GPU systems - Bonus * NVIDIA AI Enterprise * NVIDIA NIM * Triton Inference Server * vLLM * Ray Serve MLOps & AI Platform Experience - Experience with: * MLflow * Kubeflow * Model serving platforms * Vector databases * RAG deployment architectures * LLM inference systems - These align strongly with the capstone projects proposed in the curriculum. Preferred Certifications Strongly Preferred * Kubernetes Administrator (CKA) * Kubernetes Application Developer (CKAD) ## Description WeCloudData is seeking an experienced AI Infrastructure Operations Instructor to deliver a hands-on bootcamp focused on GPU-enabled AI systems, Kubernetes operations, AI deployment, observability, and infrastructure monitoring. The instructor will train students to deploy, operate, monitor, and troubleshoot AI workloads in modern cloud and data center environments. This role focuses on the infrastructure and operational side of AI systems rather than AI model development or research. The ideal candidate has experience operating production AI platforms, deploying containerized applications, managing Kubernetes environments, and working with GPU-enabled infrastructure. The instructor should be comfortable teaching beginners and helping students transition into AI Infrastructure Operations, MLOps, and AI Platform Engineering careers., Instruction & Delivery * Deliver instructor-led lectures and workshops * Conduct hands-on labs and troubleshooting exercises * Mentor students throughout the bootcamp * Support students in completing capstone projects * Evaluate assignments and provide technical feedback Curriculum Coverage - Teach topics including: * AI infrastructure fundamentals * Training vs inference workloads * GPU fundamentals and operations * Linux administration * Python scripting * Containerization using Docker * AI model deployment and serving * Kubernetes operations * GPU workload scheduling * Monitoring and observability * AI platform operations * AI infrastructure troubleshooting * AI data center fundamentals - The instructor should be capable of guiding students through all major topics outlined in the bootcamp curriculum. Lab Management * Prepare cloud-based lab environments * Configure Kubernetes clusters * Manage GPU-enabled infrastructure * Support Docker and container deployment labs * Create troubleshooting scenarios and exercises * Maintain capstone project environments ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Docker exec without Docker](https://www.wearedevelopers.com/videos/1094-docker-exec-without-docker) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? 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