DevOps Developer

CI/CD, Build & Release Automation

• Design, maintain, and improve CI/CD pipelines using tools such as Jenkins, Bitbucket, Gradle, and related technologies.
• Improve build reliability, pipeline performance, test automation integration, and release automation.
• Support development teams in improving their software delivery workflows.
• Troubleshoot complex build, deployment, and environment issues.
• Contribute to standardization and reuse of pipeline patterns across teams.
• Improve deployment repeatability, traceability, and auditability.

Cloud-Native Platform Engineering

• Support and improve Kubernetes-based deployment and runtime environments.
• Work with containerization technologies such as Docker and Kubernetes.
• Develop and maintain automation for infrastructure, environments, and deployment workflows.
• Contribute to infrastructure-as-code and configuration-as-code practices.
• Support the adoption of GitOps and declarative deployment models.
• Help improve scalability, resilience, and maintainability of cloud-native systems.
• Collaborate with Managed Services and Services teams to ensure platform capabilities are operable and supportable.

DevSecOps & Compliance Automation

• Integrate security controls into CI/CD pipelines and development workflows.
• Support vulnerability scanning, dependency checks, container image scanning, secrets management, and policy enforcement.
• Collaborate with Security and Architecture teams to improve secure software delivery.
• Help ensure pipelines and automation support auditability, traceability, and compliance requirements.
• Promote secure-by-design practices within DevOps and development teams.

Observability, Reliability & Operational Feedback

• Improve observability through metrics, logs, traces, dashboards, and alerting.
• Support incident analysis, root-cause investigation, and operational improvements.
• Work with Managed Services and Services teams to translate operational feedback into better automation, monitoring, deployment practices, and documentation.
• Identify recurring operational issues and automate solutions where possible.
• Contribute to performance, reliability, and scalability improvements.

AI-Enabled Engineering Workflows

• Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation, automation, and pipeline analysis.
• Identify practical use cases for AI in CI/CD, DevSecOps, observability, incident analysis, and developer workflows.
• Validate AI-generated code, scripts, configurations, and recommendations through proper engineering review and testing.
• Help define safe usage patterns and guardrails for AI-assisted DevOps work.
• Collaborate with development teams to integrate AI-assisted tools into the software delivery lifecycle.

Qualifications:

• 4+ years of experience in DevOps, platform engineering, infrastructure engineering, or software delivery automation.
• Strong hands-on experience with CI/CD pipelines and automation.
• Experience with Jenkins, Bitbucket, Gradle, Git, and related development tooling.
• Experience with Docker, Kubernetes, and cloud-native deployment patterns.
• Good understanding of infrastructure-as-code, configuration management, and automation.
• Knowledge of GitOps concepts and tools such as ArgoCD, Flux, or similar.
• Understanding of DevSecOps principles and security automation in CI/CD pipelines.
• Experience with observability tools and practices, including logs, metrics, dashboards, and alerting.
• Strong troubleshooting and problem-solving skills.
• Ability to work independently and take ownership of technical topics.
• Good communication skills and ability to collaborate across distributed teams.
• Understanding of AI tools and their application in DevOps, software development, and operational workflows.
• Relevant certifications such as AWS Cloud Practitioner, AWS Certified Solutions Architect, ITIL, CISSP, or CISM.
• Experience with AWS, Azure, GCP, or hybrid cloud environments.
• Experience with Helm, Terraform, Ansible, or similar tooling.
• Experience with Prometheus, Grafana, ELK/OpenSearch, or comparable observability platforms.
• Experience with incident response, production support, managed services enablement, performance tuning, or operational reliability.
• Knowledge of progressive delivery techniques such as feature flags, canary releases, blue-green deployments, and automated rollback.
• Experience with AI-assisted development tools, coding assistants, or AI-based automation in enterprise engineering environments.