Senior Digital DevOps Engineer

We are seeking a Senior Digital DevOps Engineer to join our Digital Web and Mobile DevOps team. In this role, you will serve as a technical leader and hands-on engineer responsible for designing, evolving, and operating the platforms that power modern web and mobile product delivery at enterprise scale.

You will lead the transition from legacy DevOps tooling to modern, cloud-native CI/CD platforms, championing automation-first practices, standardised pipelines, and self-service developer experiences. You will influence engineering culture, drive architectural decisions across delivery infrastructure, and partner closely with development, QA, security, and cloud engineering teams to unlock speed, quality, and reliability at scale.

The ideal candidate combines deep hands-on expertise with system-level thinking, thrives on solving complex delivery problems, and is passionate about applying AI- assisted engineering practices to further amplify team productivity and release velocity.

The candidate will have responsibilities across the following functions:

CI/CD Pipeline Design and Optimisation:

• Design, build, and continuously optimise enterprise-grade CI/CD pipelines using GitLab CI/CD, Jenkins, and self-hosted/managed runners.
• Lead the modernisation and consolidation of legacy pipelines into standardised, reusable, template-driven workflows (e. g., shared libraries, GitLab CI templates, reusable YAML components).
• Define and enforce pipeline governance patterns, including branching strategies, artefact promotion models, and environment gating.
• Improve pipeline performance, reliability, and observability, reducing lead time, mean time to recovery (MTTR), and build/test cycle times.

Automation Across Build, Test, Deployment and Infrastructure:

• Architect and implement automation frameworks spanning build, test, deployment, provisioning, and post-release verification.
• Automate repetitive engineering toil and eliminate manual handoffs across the software delivery lifecycle.
• Establish release automation patterns including blue/green, canary, and progressive delivery strategies for web and mobile workloads.
• Integrate configuration management, secrets management, and environment orchestration into fully automated flows.

Cloud and Infrastructure Engineering:

• Design, provision, and manage AWS-based infrastructure using Terraform and modern Infrastructure-as-Code (IaC) practices.
• Own and standardise environment management (dev, test, staging, pre-prod, prod) including ephemeral/on-demand environments for feature workflows.
• Apply cloud engineering best practices for cost optimisation, tagging, network segmentation, resilience, and disaster recovery.
• Contribute to platform reference architectures that development teams consume via self-service.

Code Quality and Security:

• Embed quality and security gates directly into pipelines using SonarQube, SAST, SCA, secrets scanning, and container/image scanning tools.
• Define and operationalise DevSecOps governance policies, including quality thresholds, vulnerability SLAs, and license compliance rules.
• Partner with security engineering to implement shift-left security practices and remediation feedback loops for developers.
• Continuously evolve quality baselines and enforce compliance without slowing developer velocity.

Mobile and Web DevOps Practices:

• Build and operate mobile CI/CD workflows for iOS and Android, including signing, provisioning, versioning, distribution, and app store deployment.
• Integrate device farms (cloud and on-prem) and mobile automation frameworks (e. g., Appium, XCUITest, Espresso) into pipelines.
• Standardise web application delivery including static asset builds, containerization, CDN publishing, and progressive web deployment strategies.
• Support cross-platform test orchestration, parallelisation, and reporting for both web and mobile products.

Developer Enablement and DevOps Standardisation:

• Champion self-service developer experiences through paved-road pipelines, golden templates, internal developer portals, and CLI-driven tooling.
• Define and roll out enterprise DevOps standards, patterns, and reference implementations consumed by multiple product teams.
• Provide technical leadership, mentorship, and coaching to engineers across product teams on modern DevOps practices.
• Drive cross-team collaboration with platform, cloud, security, QA, and product engineering to align delivery practices at scale.

AI as a Supporting Capability:

• Integrate AI-assisted engineering tools into the developer workflow to enhance productivity, not replace engineering judgment.
• Leverage AI for: Code generation to accelerate boilerplate, IaC, and pipeline scaffolding. Test generation: auto-produce unit, integration, and regression test
• coverage. Documentation: generate and maintain up-to-date pipeline, service, and runbook documentation. Pipeline optimization analyze telemetry to identify bottlenecks, flaky tests, and improvement opportunities.
• Establish responsible-use guardrails, prompt patterns, and governance for AI- assisted development across the DevOps landscape.
• The following tooling categories represent the technology landscape the role operates within. Specific tools may vary by product portfolio.
• Category Representative Tools: CI/CD Tools, GitLab CI/CD, Jenkins, GitLab Runners (shared, group, project), pipeline templates.
• Cloud and Infrastructure: AWS (EC2 ECS, EKS, S3 IAM, Lambda, CloudFront, CloudWatch), Terraform, Kubernetes, Docker, Helm, Automation / Testing, Frameworks: Appium, Selenium, XCUITest, Espresso, Cypress, Playwright, JUnit, TestNG, Postman/Newman, Artefact Management, JFrog Artifactory, Sonatype Nexus, GitLab Package Registry, Amazon ECR.
• Code Quality and Security: SonarQube, SAST tools, SCA/dependency scanners, secrets scanning, container image scanning.
• Source Control: Git, GitLab, GitHub, branching strategies (trunk-based); Scripting Languages: Bash, Python, Groovy, PowerShell, YAML, HCL.
• Mobile / Web Tooling: Fastlane, Gradle, Xcode Build System, CocoaPods, npm/yarn, Webpack/Vite, cloud device farms, AI-assisted.
• Development Tools: GitHub Copilot, GitLab Duo, AI-driven test generation, AI- based code review, LLM-powered documentation generators.

Requirements:

• 5+ years of hands-on DevOps engineering experience in enterprise environments, with a track record of owning production-grade delivery platforms end-to-end.
• Deep CI/CD expertise with GitLab CI/CD and/or Jenkins, including pipeline design patterns, runner management, reusable templates, and pipeline performance optimisation.
• Strong cloud and infrastructure experience on AWS, with practical proficiency in Terraform and Infrastructure-as-Code practices.
• Proven experience designing and operating automation frameworks across build, test, deployment, and infrastructure provisioning.
• Hands-on experience with code quality and security tooling, including SonarQube, SAST, SCA, dependency scanning, and integrating them as pipeline gates.
• Strong scripting and programming skills, proficient in at least two of: Python, Bash, Groovy, PowerShell, plus YAML/HCL for infrastructure and pipeline definition.
• Experience modernising legacy CI/CD environments and driving migrations to modern, standardised, and self-service platforms.
• Demonstrated ownership and technical leadership, leading initiatives, mentoring engineers, and driving cross-team engineering standards.
• Solid understanding of Git-based workflows, branching strategies, and code review practices at scale.
• Excellent problem-solving, communication, and collaboration skills, with the ability to influence engineering teams across the organisation.
• The following capabilities are not required but will distinguish exceptional candidates: AI-assisted development experience, including hands-on use of tools such as GitHub Copilot, GitLab Duo, or equivalent LLM-based engineering assistants for code, test, and documentation generation, as well as pipeline optimisation.

Technical Skills:

• CI/CD Platforms: GitLab CI/CD (Templates, Runners, Shared Libraries), Jenkins, GitHub Actions.
• Cloud and Infrastructure: AWS (EKS, ECS, EC2 S3 CloudFront, IAM, Lambda, CloudWatch), Terraform, Kubernetes, Docker, Helm.
• Mobile and Web Tooling: Fastlane, Gradle, Xcode Build, npm/yarn, Webpack, Vite, Cloud Device Farms.
• Automation and Testing: Appium, Selenium, XCUITest, Espresso, Cypress, Playwright, Postman.
• Code Quality and Security: SonarQube, SAST, SCA, Secrets Detection, Container Image Scanning, Artefact repositories (JFrog, Nexus).
• Languages and Scripting: Python, Bash, Groovy, HCL, YAML, PowerShell.
• AI-Assisted Engineering: GitHub Copilot, GitLab Duo, LLM prompt engineering for IaC scaffolding, test generation, and runbook automation.