PowerShell) Monitoring: Grafana, Prometheus, ELK, Splunk Agile working and tooling (e.g., Jira, Confluence) Diagnosing and resolving complex system issues ITIL knowledge or exposure to IT service operations Containerisation: Docker, Kubernetes, OpenShift Awareness of modern tech trends and tooling Security Requirements UKIC DV clearance holder only Why Apply? Join a forward-thinking SRE team in an environment where your work directly More ❯
Ensure compliance and audit readiness Requirements Proven delivery of Microsoft CAF landing zones Hands-on engineering leader Experience in regulated industries (finance, banking, insurance) Skills Terraform, CI/CD, Kubernetes Profile Pragmatic, execution-focused, resilient - a doer, not just a strategist More ❯
Isleworth, London, United Kingdom Hybrid / WFH Options
Lancesoft Ltd
strong focus on automated testing (unit, integration, functional, end-to-end, visual regression, Lighthouse). Collaborate on DevOps practices: CI/CD (Jenkins, Concourse ), containerisation, Helm chart authoring, and Kubernetes deployments. Work within a cross-functional Agile team, contributing to technical direction, code reviews, and process improvements. Ensure code is performant, secure, observable, and aligned with best practices. Mentor and … Node.js in production environments. Strong knowledge of GraphQL (API design, schema evolution, integration ). Experience with automated testing frameworks ( Vitest, Playwright, Jest ). Familiarity with DevOps tooling: Docker, Helm, Kubernetes , CI/CD pipelines. Experience with cloud-native architectures and infrastructure-as-code. Ability to drive improvements across the codebase and influence technical direction. Experience mentoring and coaching developers. Bonus More ❯
scale the machine learning platform, ensuring it supports high-throughput model inference and fast iteration cycles. This position is perfect for someone who thrives at the intersection of MLOps, Kubernetes, and cloud infrastructure, with a hands-on approach to solving complex challenges. You will work closely with ML engineers and product teams to align infrastructure with evolving project needs, research … cutting-edge MLOps practices, and mentor colleagues by sharing expertise in cloud operations and ML engineering best practices. The right candidate will also be responsible for managing GPU-powered Kubernetes clusters, improving automation pipelines, and ensuring system reliability. Candidates should have experience building and managing Kubernetes clusters from scratch, configuring them manually using tools like kubeadm, and deploying applications with … Helmdemonstrating true infrastructure-level expertise rather than just deploying services on managed platforms. Key Skills MLOps & Kubernetes: GPU-enabled cluster management, built from scratch using kubeadm and Helm. Programming : Python or Go for ML automation workflows. Containerization : Docker and containerized application deployment. Cloud : AWS experience supporting ML workloads. CI/CD & Automation : ArgoCD, GitHub Actions, Infrastructure-as-Code (Terraform). More ❯
