4 of 4 Contract Google Kubernetes Engine Jobs in the South East

experience in designing and executing large-scale cloud migration projects. Deep expertise in Google Cloud Platform, with extensive hands-on experience in Google Kubernetes Engine (GKE). Experience with containerization technologies, CI/CD pipelines, and Infrastructure as Code (IaC) tools like Terraform. Strong understanding of network architecture, security best practices, and FinOps principles in a … cloud context. Implementing and managing GKE security features such as Workload Identity, Pod Security Policies (or the newer Pod Security Admission controller), and GKE Sandbox. Establishing robust IAM policies for GKE and related GCP services. More ❯

reliability and efficiency. Asynchronous Programming: Implement and manage asynchronous workflows and concurrent processes. Containerization: Utilize Docker to containerize applications for deployment. Cloud Deployment & Operations: Deploy and troubleshoot applications on Google Cloud Platform (GCP). Candidates must be able to diagnose production issues within cloud environments (e.g., Cloud Run, GCS, BigQuery). Infrastructure as Code: Develop and manage cloud infrastructure … in that environment. Database Skills: High proficiency in SQL . Nice-to-Have Skills Direct production experience with FastAPI . Experience with Google Cloud Run and Kubernetes (GKE) . Familiarity with GCP data tools like BigQuery and Google Cloud Storage (GCS) . Experience building complex agentic AI applications (beyond basic RAG or LangChain implementations). How We More ❯

/LLMOps, and cloud-native architecture . The candidate must have recent experience implementing data science solutions in Databricks and be comfortable deploying web applications via containerized workflows (Docker, Kubernetes). This role involves building scalable AI/ML systems, deploying LLMs, and operationalizing models in production. Key Responsibilities: Design, develop, and deploy ML, Deep Learning, and LLM solutions. … and monitoring. Architect secure ML/AI systems on Azure, AWS, or GCP . Deploy containerized web apps and ML services using Docker, Kubernetes (AKS/EKS/GKE), Azure Container Apps, ECS , integrated with CI/CD (GitHub Actions, Azure DevOps, Jenkins). Mentor engineers, enforce best practices, and lead design/architecture reviews. Required Skills & Experience: 5+ …/CD, and model monitoring experience. Proficiency in Python, PyTorch/TensorFlow, FastAPI/Flask . Cloud architecture experience: Azure preferred, AWS/GCP acceptable . Skilled in Docker, Kubernetes, Helm, Terraform, IaC for deploying ML and web apps. More ❯

in code review processes. Collaborating with frontend engineers to define interfaces and deliver product features. Working with DevOps/Platform teams on CI/CD, containerisation and deployment (Docker, Kubernetes or managed alternatives). Troubleshooting production issues and improving observability (logging, metrics, tracing). Contributing to technical design discussions and driving improvements to reliability and performance. Tech Stack & Skills … development practices and experience with pytest or equivalent. Experience working with RESTful APIs and/or GraphQL. Familiarity with containerisation and cloud deployment (Docker, Kubernetes/EKS/GKE or equivalent). Version control with Git and experience of CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI, etc.). Nice to have: Experience with async frameworks (FastAPI, Celery More ❯