DevOps Engineer

Glow connects capital to customers through trusted brands. Our embedded fintech platform lets mobile operators, OEMs, and consumer electronics retailers offer device finance, insurance, and trade-in at the point of sale, serving partners across EMEA, AMERS, and APAC. We're at an inflection point: evolving from a conventional lending platform into an AI-native embedded FinTech platform built to serve tens of millions of customers. Over the next 24–36 months we're rebuilding how the company operates, and the infrastructure and tooling our engineers build is what makes AI-enabled processes, AI-augmented decisioning, and AI-native operations viable at the unit economics this business requires.

About the Role

We're hiring a DevOps Engineer to design, automate, and maintain the cloud infrastructure that powers our platform — and, increasingly, the infrastructure that powers our AI and data capabilities. You'll own our Kubernetes environments, build and harden CI/CD pipelines, manage secure private networking on Azure, and act as a key troubleshooter when applications or pipelines misbehave. Just as importantly, you'll help lay the operational and tooling foundation that our data, applied science, and ML work depends on, and you'll look for opportunities to replace manual toil with automated, AI-augmented processes. This is a hands-on role with genuine strategic weight rather than incremental impact.

What You'll Do

• Manage and maintain Kubernetes clusters (preferably Azure Kubernetes Service), including workload scheduling, resource sizing, scaling, upgrades, and overall cluster health — including workloads that serve data pipelines and ML/AI services.
• Build, optimize, and troubleshoot CI/CD pipelines across Azure DevOps, GitHub Actions, and Octopus Deploy, automating builds, tests, and deployments to production.
• Design and operate secure private networking on Azure, including private endpoints, private VNets, network security groups, and hub-and-spoke topologies — important given the sensitivity of financial and customer data.
• Implement and maintain application monitoring, logging, and operational instrumentation using tools such as Datadog and Azure Log Analytics, giving the business the platform-wide visibility our AI-native operations depend on.
• Diagnose and resolve incidents — from application crashes to pipeline failures — quickly identifying root cause and driving the fix.
• Build and maintain infrastructure as code (Terraform, ARM, and/or Ansible) to keep environments consistent, repeatable, and auditable.
• Identify manual, repetitive work across the engineering lifecycle and replace it with automated or AI-augmented processes, building prototypes, and moving them to production.
• Partner with development, data, and security teams to build the AI tooling and platform foundations (data accessibility, environments, deployment paths) that advanced ML/AI capability is built on.
• Collaborate closely with developers, architects, and stakeholders, and participate in on-call rotation as needed.

Required Qualifications

• 4+ years of professional DevOps, cloud, or infrastructure engineering experience.
• Strong hands‑on experience managing Kubernetes (deployment, upkeep, workload management, and right‑sizing).
• Solid experience with Microsoft Azure cloud services.
• Proven experience building CI/CD pipelines in GitHub and Azure DevOps.
• Working knowledge of private networking concepts on Azure (private endpoints, private VNets, NSGs, secure traffic routing).
• Experience with application monitoring and logging tools such as Datadog and Azure Log Analytics.
• Strong troubleshooting skills — able to independently diagnose the root cause of an application crash or pipeline failure.
• A pragmatic, automation‑first mindset and genuine enthusiasm for using AI tooling to do work that would otherwise require manual effort.
• Excellent communication skills and a genuine team‑player mindset.

Nice to Have

• Experience with infrastructure as code (Terraform, Ansible, ARM templates).
• Scripting ability in Bash, Python, or PowerShell.
• Familiarity with containerization (Docker), Helm, and secret management (e.g., Azure Key Vault, HashiCorp Vault).
• Exposure to regulated/financial environments (e.g., PCI DSS, ISO 27001) and secure TLS/certificate management.

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