1 to 25 of 282 GCP Jobs in the South East

GCP DevOps Engineer – (GCP, Google Cloud Platform, DevOps, CI/CD, GKE, Cloud Run, Cloud Build, Architecture, SRE, Kubernetes, Linux, Docker, Google) – Permanent – London/Hybrid Charles Simon Associates are recruiting for a GCP DevOps Engineer in London on an exclusive basis for our rapidly scaling business. Location: London/… deliver robust solutions. Driving cost optimisation and best practices across the GCP estate. What We’re Looking For: Hands-on experience with Google Cloud Platform (must have). Strong background in DevOps/SRE/Cloud Engineering. IaC expertise (Terraform preferred). Experience with Kubernetes/GKE and containerisation (Docker ...

version control (Git, Azure DevOps) beyond the very basics, ensuring reliable and maintainable codebases. Infrastructure & cloud: Familiarity with cloud platforms (Azure preferred; AWS or GCP also valuable), containerization (Docker, Kubernetes), and infrastructure-as-code tools like Terraform. Applied AI development: Experience working with LLM APIs (e.g., OpenAI) and building lightweight ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

software architecture. Hands-on expertise with Java, Spring Boot , and microservices. Strong understanding of Agile and DevOps practices. Familiarity with cloud platforms (AWS, Azure, GCP) and Infrastructure as Code. Experience with CI/CD, containerisation (Docker, Kubernetes), and automated testing. Excellent communication and stakeholder engagement skills. Desirable: Experience in consulting ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

Technology Officer (CTO), ensuring close alignment with our technical vision and strategic roadmap. Responsibilities Maintain and evolve cloud infrastructure, primarily on Google Cloud Platform (GCP), with some exposure to AWS and Azure Write, review, and manage modular, reusable Terraform code Operate and enhance CI/CD pipelines using GitHub Actions … modular and reusable patterns preferred) Strong foundation in Linux, networking, and container technologies Experience deploying and managing applications on at least one major cloud provider (GCP preferred; AWS or Azure acceptable) Experience working with relational databases in production environments (e.g., Postgres, MySQL), including basic performance troubleshooting, migrations, backups, and access ...

paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working with cloud-based architectures (AWS, GCP, or similar). Expertise in testing frameworks, CI/CD, and containerization technologies such as Docker or Kubernetes. Experience in managing and deploying services ...

/TypeScript, Java, C# Frameworks: Vue/Angular/React/Node/Next, Spring/Spring Boot, .NET/ASP.NET Cloud platforms: AWS, GCP, Azure CI/CD:Jenkins, GitHub Actions, Azure DevOps IaC: Terraform, CloudFormation, Azure Bicep Pragmatic and safe usage of AI through the SDLC (e.g. using ...

pipelines and infrastructure automation. Required Skills TypeScript/Node.js REST APIs (Express, Nest.js, or similar frameworks) Unit testing (Jest or equivalent) Cloud computing (GCP preferred; AWS or Azure experience also valuable) Infrastructure as Code (Terraform or similar) Docker and Compose Continuous Integration tools and environments Experience in a Continuous Delivery ...