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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
(Apply online only) 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.
