DevOps Engineer
G MASS
London, UK
10 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Amazon Web Services
Microsoft Azure
Cloud Computing
Configuration Management
Continuous Integration
DevOps
Ansible
Software Deployment
Containerization
Kubernetes
Terraform
+1 more
Docker
Job description
A start-up consultancy focused on motor finance remediation is seeking a DevOps Engineer to support the integration, deployment and operation of its AI-powered products. This role is central to ensuring reliable, secure and scalable delivery environments.
Key Responsibilities
- Design and manage CI/CD pipelines for software deployment and automation
- Collaborate with data and product teams to build and maintain scalable infrastructure
- Monitor and optimise production environments, proactively addressing issues
- Develop and enforce best practices for infrastructure-as-code and configuration management
- Implement security and compliance processes suited to financial services environments
- Maintain clear documentation for infrastructure, deployment, and operations
Requirements
- Proven experience in a DevOps or infrastructure engineering role
- Strong knowledge of cloud platforms (Azure, AWS, or GCP)
- Familiarity with containerisation (Docker, Kubernetes) and automation tools (Terraform, Ansible)
- Understanding of CI/CD, monitoring, and troubleshooting in production environments
- Strong problem-solving and collaboration skills
- Experience supporting data or AI workloads preferred
Permanent contract.
Salary to be discussed.
Seniority level
Associate
Employment type
Full-time
Job function
Consulting
Industries
Business Consulting and Services
Requirements
- Proven experience in a DevOps or infrastructure engineering role
- Strong knowledge of cloud platforms (Azure, AWS, or GCP)
- Familiarity with containerisation (Docker, Kubernetes) and automation tools (Terraform, Ansible)
- Understanding of CI/CD, monitoring, and troubleshooting in production environments
- Strong problem-solving and collaboration skills
- Experience supporting data or AI workloads preferred
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