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DevOps Engineer

Volaris Group
Remote, GBR
Full-time
Mid
Remote
Discovered 4 weeks ago
AzureAWSTerraformAzure DevOpsGitHub ActionsDocker

Full Job Posting

What You’ll Do

Cloud & Platform Engineering: Design, build and operate resilient infrastructure across both Azure and AWS, covering compute, storage, databases, networking and managed platform services. Build reusable patterns and help development teams select the right services based on performance, resilience, security, operational complexity and cost.

Infrastructure as Code: Drive automated infrastructure provisioning using modern IaC tools, with a strong preference for modular, repeatable patterns using Terraform and native cloud templates where appropriate. Ensure environments are created predictably through version control, automated validation, appropriate deployment controls and policy guardrails.

CI/CD & Software Delivery: Build and maintain delivery pipelines using platforms such as Azure DevOps and GitHub Actions. Automate build, testing, security scanning, artefact management and deployment activities, and help teams move towards smaller, repeatable and lower-risk releases.

Containers & Cloud-Native Platforms: Support containerised workloads using technologies such as Docker and managed container platforms including AKS, EKS, ECS and Azure Container Apps. Apply Kubernetes where it genuinely adds value, while recognising when a simpler managed service is the better engineering choice.

Platform Engineering & Developer Experience: Treat the internal platform as a product. Create self-service capabilities, reusable infrastructure modules, standard hosting patterns, secrets and configuration management, standard CI/CD pipelines and “golden paths” so development teams can consume cloud services without needing to become infrastructure experts.

Observability, Reliability & Operations: Improve availability and visibility across application and infrastructure layers. Build actionable monitoring, centralised logging and alerting focused on signal rather than noise. Support incident investigation, root-cause analysis, backup and recovery, resilience and disaster-recovery planning, and turn lessons from incidents into permanent engineering improvements.

Automation: Identify repetitive infrastructure, deployment and operational activities and replace them with reliable automation using technologies such as PowerShell, Python, Bash, APIs, Terraform and cloud-native tooling. Reduce operational toil and create self-service capabilities wherever practical.

Cloud Security: Partner with Security to embed security into cloud platforms and delivery pipelines, including least-privilege IAM and RBAC, workload identities, secrets and certificate management, network segmentation, secure configuration, vulnerability management, logging and auditability, and secure CI/CD. Avoid unnecessary long-lived credentials and excessive permissions.

Cloud FinOps & Cost Optimisation: Embed cost efficiency into everyday engineering decisions. Improve spend visibility and ownership, establish tagging and budget standards, detect anomalous expenditure, identify idle and underutilised resources, rightsize workloads, optimise storage, evaluate Reservations, Savings Plans and other commitment models, and improve forecasting of future cloud requirements.

Evolving for AI Workloads: Help design cloud infrastructure ready for AI-enabled applications, model and API consumption, dynamic workloads, event-driven architectures and high-performance compute. Help ensure that engineering controls, security, monitoring and cost management evolve alongside an increasingly AI-accelerated software development lifecycle.

What You’ll Bring

Hands-on Multi-Cloud Experience: Proven experience building, operating and troubleshooting workloads across both Microsoft Azure and Amazon Web Services , including compute, storage, databases, networking and managed platform services.

IaC & Automation Mindset: Strong expertise in declarative Infrastructure as Code, ideally Terraform, together with practical scripting skills using Python, PowerShell, Bash or similar technologies to eliminate repetitive operational activity.

Delivery & Source Control Expertise: Practical experience designing and maintaining continuous integration and delivery pipelines using platforms such as Azure DevOps or GitHub Actions, together with strong Git and modern source-control practices.

Networking & Security Fundamentals: Strong understanding of cloud networking including VNets/VPCs, routing, firewalls, load balancing, DNS and private connectivity, together with IAM, RBAC, workload identities and secure cloud configuration.

Observability & Reliability: Experience operating production services, including monitoring, logging, incident investigation, resilience, backup and recovery, and the ability to turn recurring operational issues into permanent engineering improvements.

Cloud FinOps: Practical understanding of cloud cost drivers and experience analysing, optimising and forecasting cloud expenditure. We’re particularly interested in candidates who can demonstrate measurable examples of reducing cloud costs without adversely affecting service quality.

Agile Collaboration: Comfortable working in cross-functional Agile, Scrum or Kanban environments, breaking work into manageable deliverables and shipping improvements continuously.

Pragmatic Problem Solver: Strong troubleshooting skills across applications, infrastructure, networking and cloud services. Able to balance speed, security, reliability, maintainability and cost, favouring operational simplicity and managed services over unnecessary complexity.

You’ll also need good communication skills and the ability to work effectively with developers, security engineers, infrastructure teams, architects and business stakeholders.

Nice to Have

Azure and/or AWS certifications.

FinOps Foundation certification or significant practical FinOps experience.

Kubernetes certification or significant Kubernetes experience.

Experience building internal developer platforms or self-service cloud capabilities.

Experience with Azure Landing Zones or AWS Control Tower.

Experience supporting AI or machine-learning workloads, including Azure AI, Azure OpenAI or Amazon Bedrock.

Experience supporting GPU or other high-performance cloud workloads.

Experience working in large, distributed or multi-business environments, particularly environments created through acquisition or organisational change.

Worker Type:

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