Engineer - Application Development

World Wide Technology (WWT) provides technology solutions spanning AI, digital, cybersecurity, cloud, and infrastructure. The Engineer will design, build, operate, and improve hybrid platform environments supporting the WWT Prototype Platform, with a focus on OpenShift, Kubernetes, GitOps-driven CI/CD, automation, observability, and shared application services. The role also provides operational support, incident response, documentation, collaboration with application and infrastructure teams, and adoption of AI-assisted engineering workflows.

Responsibilities:

• Manage and maintain Kyverno admission policies across development, test, and production environments; update image verification policies, registry allow-lists, and pod security constraints based on security requirements and operational learnings
• Administer secrets management platform; maintain policy frameworks, help teams configure and rotate secrets, and resolve credential injection failures and compliance violations
• Create and maintain Grafana dashboards and alerts tracking cluster health, resource utilization, pod scheduling, deployment throughput, and pipeline performance
• Analyze Splunk logs and observability data to identify performance bottlenecks, resource contention, and OpenShift cluster scaling opportunities; implement optimization changes (scaling policies, resource requests, queue tuning, quota management) and partner with the Infrastructure team on capacity planning recommendations (Infrastructure owns cluster management, but you drive observability-based improvements)
• Monitor and optimize GitHub Actions runner performance; maintain runner pools across multiple scale sets, diagnose queue buildup and job failures, implement capacity improvements
• Debug and improve ArgoCD and Codefresh pipeline reliability; trace deployment failures from CI through GitOps sync, resolve race conditions, and enhance pipeline architecture based on user patterns
• Maintain technical runbooks and troubleshooting guides for common platform issues (policy blocks, deployment failures, secrets issues, registry access, runner problems, etc.; keep documentation current as platform evolves
• Respond to platform support requests via the ServiceNow queue — troubleshoot deployment failures, authentication issues, policy blocks, platform access issues, and user environment misconfigurations, escalating complex issues appropriately
• Collaborate with application teams, security/policy owners, and cluster operations on cross- cutting platform concerns
• Participate in incident response and root cause analysis when critical platform issues impact multiple users; follow established operational procedures
• This role requires comfort working alongside AI‑powered tools while maintaining strong engineering judgment, validation, and accountability for outcomes; engineers are expected to contribute to the adoption and continuous improvement of AI‑enabled workflows by providing feedback and identifying new opportunities for automation
• Engineers are expected to actively use approved AI tools and agents to assist with platform operations, troubleshooting, automation, and documentation under established governance and best practices, as part of their day‑to‑day work
• Engineers will create and maintain AI skills that abstract the consumption of the WWT Prototype customer base, allowing them to agentically interact with the platform

Requirements:

• 3–5 years of progressive experience in DevOps, platform engineering, SRE, or
  infrastructure roles
• Hands-on experience managing Kubernetes and Red Hat OpenShift clusters in
  production environment
• Demonstrated experience with Kyverno or similar admission control / policy enforcement
  tools
• Demonstrated experience with service mesh architectures, traffic management, or load
  balancing in Kubernetes environments
• Experience building and maintaining CI/CD pipelines and automation workflows using
  tools such as GitHub, GitHub Actions, Jenkins, Codefresh, APIs, and GitOps-based
• Experience with monitoring and observability tools (Prometheus, Grafana) and log
  analysis (Splunk, ELK, or similar)
• Hands-on Linux system administration and troubleshooting skills
• Strong problem-solving ability; comfort debugging distributed systems and complex
  deployment failures
• Comfort scripting or coding in languages such as Shell, Python, or Node.js
• Effective communication skills — ability to explain technical concepts to non-technical users and document issues clearly
• Comfort with rapid context-switching between reactive support and proactive
  optimization work
• A self-starter mindset with strong ownership, organization, and a passion for learning new technologies