We are hiring a DevOps Engineer to own the engineering foundations underneath Boud's delivery: the pipelines that ship code, the environments teams build and test in, and the cloud infrastructure that keeps our platforms stable once they are live. The role sits in Engineering and reports to the Technical Lead, with a functional line to the Solutions Architect on assigned projects.
This is a hands‑on delivery role, not an infrastructure administration one. You will design and run CI/CD pipelines, provision cloud environments as code, automate deployments across development, testing, staging, and production, and put in place the monitoring and alerting that tells us a problem is forming before a client does. You will move between our own products and client platforms, adapting to different stacks and different cloud estates, and you will be accountable for the security, repeatability, and reliability of everything that reaches production.
Much of our delivery serves government, semi‑government, and regulated clients. Infrastructure decisions are therefore made with data residency, access control, and compliance obligations understood at the start — not retrofitted the week before a security review. You will work alongside software engineers, technical leads, solutions architects, and project managers, and you will engage directly with client‑side technical and cybersecurity teams, where explaining a decision clearly matters as much as making it.
KEY RESPONSIBILITIES
PIPELINES & RELEASE ENGINEERING
- Design, build, and maintain CI/CD pipelines for Boud's internal products and client platforms using Azure DevOps, GitHub Actions, or GitLab CI.
- Automate build, test, and deployment workflows, including release gating, rollback paths, and low-downtime deployment patterns.
- Support release management across concurrent projects — coordinating deployment windows, dependencies, and go‑live activity with project managers and client teams.
CLOUD INFRASTRUCTURE & AUTOMATION
- Provision, configure, and manage cloud infrastructure on Azure, AWS, or GCP, with attention to cost, performance, and data‑residency requirements.
- Define infrastructure as code using Terraform or an equivalent tool, keeping environment configuration versioned, reviewable, and reproducible.
- Containerize applications with Docker and operate orchestrated workloads where Kubernetes or a managed container service is in use.
- Build and maintain development, testing, staging, and production environments, keeping parity between them and clearing environment issues that block delivery teams.
RELIABILITY, MONITORING & INCIDENT RESPONSE
- Implement logging, monitoring, alerting, and dashboards using tools such as Prometheus, Grafana, the ELK stack, Azure Monitor, or CloudWatch.
- Monitor performance, availability, and capacity, and act on degradation before it reaches users — including event‑driven load spikes on platforms such as Hackify.
- Troubleshoot infrastructure and deployment failures, participate in incident response, and lead structured root‑cause analysis with follow‑up actions that actually close.
- Establish and test backup, retention, and disaster recovery procedures for the platforms in your scope.
SECURITY & COMPLIANCE
- Apply secure‑by‑default practices across pipelines and infrastructure: secrets management, least‑privilege IAM, certificate handling, network segmentation, and patching.
- Support client security reviews, audits, and compliance requirements, including NCA Essential Cybersecurity Controls and PDPL obligations where they apply.
COLLABORATION & ENGINEERING STANDARDS
- Work with software engineers, technical leads, and solutions architects to make applications straightforward to deploy, observe, and operate.
- Interface with client technical, infrastructure, and cybersecurity teams through onboarding, integration, security review, and handover.
- Document infrastructure design, deployment runbooks, environment configuration, and incident procedures so knowledge transfers cleanly between projects and to clients.
- Build Boud's shared DevOps standards — reusable pipeline templates and reference infrastructure patterns — so each new project starts further ahead than the last.
What we are looking for
MUST-HAVE
- 4-6 years of professional experience, including at least 3 years in a dedicated DevOps, platform, or cloud infrastructure role.
- Strong Linux administration and command‑line proficiency.
- Proven experience building and maintaining CI/CD pipelines in Azure DevOps, GitHub Actions, GitLab CI, or Jenkins.
- Hands‑on production experience with at least one major cloud — Azure, AWS, or GCP — across compute, networking, storage, and identity.
- Practical experience with Docker and containerised deployment.
- Working knowledge of Infrastructure as Code with Terraform, Bicep, ARM, or CloudFormation.
- Scripting and automation in Bash and Python, or a comparable language.
- Solid networking fundamentals: DNS, TCP/IP, HTTP/HTTPS, load balancing, reverse proxies, firewalls, and VPNs.
- Operational database experience — deployment, backup, restore, and basic performance troubleshooting.
- Experience implementing monitoring, logging, and alerting in production, and using it during live incidents.
- Sound security practice: secrets management, least‑privilege access, TLS, and secure configuration.
- Bachelor's degree in Computer Science, Software Engineering, IT, or a related field — or equivalent proven experience.
- Professional working proficiency in English; Arabic is an advantage for client‑facing work.
NICE-TO-HAVE
- Azure DevOps at enterprise scale — boards, repos, pipelines, and artifact management.
- Production Kubernetes (AKS, EKS, GKE, or self‑managed), including Helm.
- Advanced Terraform practice: modules, remote state, and multi‑environment workspaces.
- Cloud certification such as Azure Administrator or DevOps Engineer Expert, AWS SysOps or DevOps Engineer, or CKA.
- Government or semi‑government clients, and familiarity with NCA ECC, PDPL, or similar frameworks.
- Experience working in Saudi Arabia or the wider GCC.
- Consulting, digital transformation, or technology services background with concurrent client projects.
- Deploying AI/ML workloads — model serving, inference endpoints, or LLM‑backed services.