Devops jobs in United Kingdom

GCP DevOps Engineer - AI Infrastructure (Financial Services)
Location: London
Contract Type: Full-time / Permanent

2 days required at Office and 3 from home per week

£60000 - 80000 DOE

Join a forward-thinking financial services firm leveraging AI to transform decision-making and customer experiences. We're seeking a skilled GCP DevOps Engineer to architect and maintain cloud-native infrastructure that supports high-performance AI systems. This is a hands-on technical role with strategic impact across infrastructure, automation, and security.

Infrastructure & Cloud Engineering

• Design, build, and manage scalable, resilient infrastructure on Google Cloud Platform (GCP).
• Implement Infrastructure as Code (IaC) using Terraform to ensure consistent and secure deployments.
• Utilize GCP services such as Compute Engine, Cloud Run, Cloud Functions, BigQuery, and Kubernetes to support AI workloads.

CI/CD & Automation

• Develop and maintain CI/CD pipelines using Google Cloud Build, Jenkins, and GitHub Actions.
• Automate deployment workflows and operational tasks to improve efficiency and reduce manual errors.
• Drive adoption of DevOps best practices across engineering teams.

Containerization & Orchestration

• Build and manage containerized applications using Docker and orchestrate them with Kubernetes.
• Ensure high availability and scalability of AI services through robust orchestration strategies.

Monitoring & Reliability

• Set up monitoring and alerting systems using Cloud Monitoring, Cloud Logging, Prometheus
• Troubleshoot infrastructure issues and ensure minimal downtime for critical AI services.

• Strong hands-on experience with GCP services: Compute Engine, Kubernetes, Cloud Storage, BigQuery, Cloud Run.
• Proficient in scripting with Python or Bash.
• Deep understanding of Docker and Kubernetes for containerization and orchestration.
• Expertise in CI/CD tools: Google Cloud Build, Jenkins, GitHub Actions.
• Proven experience with Terraform and other IaC tools.
• Experience in multi-cloud environments.
• Familiarity with monitoring tools such as Prometheus
• Exposure to AI/ML infrastructure and data workflows in financial services.

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