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.
Key Responsibilities
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.
Required Skills
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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