Cloud & AI Platform Engineer

• Build and operate secure, reusable infrastructure across Azure, AWS, on-premises data centers, and Oracle environments to support application teams’ access to internal systems, GitHub-based source control, and standardized deployment pipelines
• Support and accelerate the migration of internal applications from VMware to Kubernetes-based containerization, enabling workload portability across cloud and on-prem environments
• Help mature the organization’s Infrastructure-as-a-Service model enabling developers to request compute resources (e.g., CPUs) via ServiceNow with automated provisioning on the back end (a longer-term, 1 2 year capability build)
• Extend and enhance existing Terraform and Ansible automation to support additional developers and teams adopting the platform and Kubernetes deployment model
• Support GitHub-based deployment workflows, helping teams commit and deploy code through automated CI/CD pipelines
• Provide foundational support for AI infrastructure including cloud and potentially on-premises AI workloads understanding containerization, deployment, and infrastructure needs for AI systems (application-level AI development is not required)
• Help establish practical infrastructure and platform standards while the organization’s broader AI governance and data strategy are still being defined
• Act as a platform owner who can reduce recurring operational dependency on the existing infrastructure leadership team, and help train internal staff on platform and AI infrastructure best practices

• Strong hands-on experience with Kubernetes in multi-cloud environments
• Experience with Azure and AWS (Oracle Fusion Cloud ERP exposure is a plus but not required this can be learned on the job)
• Experience with enterprise landing zones
• Proficiency with Terraform and Ansible (or comparable IaC/automation tools)
• Experience with DevOps/CI-CD pipeline design and operations, ideally with GitHub-based workflows
• Understanding of foundational AI infrastructure concepts cloud AI services, containerized AI workloads, and deployment patterns (not application-level AI/ML development)
• Comfort operating in ambiguous, evolving environments where governance and standards are still being established
• Strong communication skills this role will need to train and enable other team members over time
• Background in platform engineering / cloud infrastructure engineering / DevOps engineering more so than traditional application development

Nice to Have:

• Familiarity with Microsoft Copilot and Microsoft-centric development ecosystems
• Experience with ServiceNow-integrated provisioning workflows
• Experience operationalizing on-premises AI infrastructure to reduce cloud/token costs